Semi-Supervised Classification with Graph Convolutional Networks

Abstract

We present a scalable approach for semi-supervised learning on graph-structured data that is based on an efficient variant of convolutional neural networks which operate directly on graphs. We motivate the choice of our convolutional architecture via a localized first-order approximation of spectral graph convolutions. Our model scales linearly in the number of graph edges and learns hidden layer representations that encode both local graph structure and features of nodes. In a number of experiments on citation networks and on a knowledge graph dataset we demonstrate that our approach outperforms related methods by a significant margin.

Published as a conference paper at ICLR 2017

References in corpus (2)

• Learning Convolutional Neural Networks for Graphs
• The Weisfeiler-Lehman Method and Graph Isomorphism Testing

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• Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
• A literature survey of matrix methods for data science
• EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks
• Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks
• Understanding Negative Sampling in Graph Representation Learning
• Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules
• Graph Policy Network for Transferable Active Learning on Graphs
• Understanding and Resolving Performance Degradation in Graph Convolutional Networks
• HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding
• Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph Networks
• Graph Signal Restoration Using Nested Deep Algorithm Unrolling
• Graph Random Neural Network for Semi-Supervised Learning on Graphs
• Deep Learning for Optical Tweezers
• Hybrid Quantum-Classical Graph Convolutional Network
• Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
• A Survey of Knowledge Enhanced Pre-trained Models
• Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
• RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network
• Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching
• Coupled Layer-wise Graph Convolution for Transportation Demand Prediction
• Streaming Graph Neural Networks
• GLMNet: Graph Learning-Matching Networks for Feature Matching
• What graph neural networks cannot learn: depth vs width
• GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension
• Graph Convolutional Networks based on Manifold Learning for Semi-Supervised Image Classification
• Video action detection by learning graph-based spatio-temporal interactions
• ROD: Reception-aware Online Distillation for Sparse Graphs
• Temporal Knowledge Graph Forecasting with Neural ODE
• Expressive Power of Invariant and Equivariant Graph Neural Networks
• Efficient Representation Learning Using Random Walks for Dynamic Graphs
• Social-IWSTCNN: A Social Interaction-Weighted Spatio-Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios
• Hierarchical stochastic graphlet embedding for graph-based pattern recognition
• Permutation Invariant Graph Generation via Score-Based Generative Modeling
• Adversarial Attack on Hierarchical Graph Pooling Neural Networks
• Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
• GraphDefense: Towards Robust Graph Convolutional Networks
• Federated Graph Learning -- A Position Paper
• Poincaré Wasserstein Autoencoder
• A Baseline for Few-Shot Image Classification
• Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
• Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection
• Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels
• Embedding API Dependency Graph for Neural Code Generation
• Automated Self-Supervised Learning for Graphs
• Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
• Mutual Graph Learning for Camouflaged Object Detection
• A Joint Graph and Image Convolution Network for Automatic Brain Tumor Segmentation
• Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective
• Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
• Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding
• Adversarial Defense Framework for Graph Neural Network
• Gophormer: Ego-Graph Transformer for Node Classification
• Graph Element Networks: adaptive, structured computation and memory
• Linkage Based Face Clustering via Graph Convolution Network
• Can Adversarial Network Attack be Defended?
• Distilling Knowledge from Graph Convolutional Networks
• GraphCrop: Subgraph Cropping for Graph Classification
• Probabilistic Dual Network Architecture Search on Graphs
• Graph Policy Gradients for Large Scale Robot Control
• Morphological Error Detection in 3D Segmentations
• Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition
• Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training
• Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles
• GraphPAS: Parallel Architecture Search for Graph Neural Networks
• Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment
• Automatic Symmetry Discovery with Lie Algebra Convolutional Network
• Differentiable Scaffolding Tree for Molecular Optimization
• Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction
• Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
• Counterfactual Multi-Agent Reinforcement Learning with Graph Convolution Communication
• Multi-Task Graph Autoencoders
• Graph Condensation for Graph Neural Networks
• Multi-hop Convolutions on Weighted Graphs
• Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations
• DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting
• BERT Learns (and Teaches) Chemistry
• A Behavioral Approach to Visual Navigation with Graph Localization Networks
• Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
• An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
• Residual or Gate? Towards Deeper Graph Neural Networks for Inductive Graph Representation Learning
• KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs
• Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders
• Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
• The Parallelism Motifs of Genomic Data Analysis
• Investigating and Modeling the Dynamics of Long Ties
• Action Sequence Augmentation for Early Graph-based Anomaly Detection
• Learning to Count Isomorphisms with Graph Neural Networks
• Improving Semantic Segmentation via Decoupled Body and Edge Supervision
• Beyond Graph Convolutional Network: An Interpretable Regularizer-centered Optimization Framework
• Intrinsic Relationship Reasoning for Small Object Detection
• Reasoning Over Semantic-Level Graph for Fact Checking
• Automatic Meta-Path Discovery for Effective Graph-Based Recommendation
• Neural Predictor for Neural Architecture Search
• HONEM: Learning Embedding for Higher Order Networks
• View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose
• InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
• Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation
• Representation Learning for Electronic Health Records
• Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
• Bridging Knowledge Graphs to Generate Scene Graphs
• PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
• PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
• An Autonomous Free Airspace En-route Controller using Deep Reinforcement Learning Techniques
• GNN-LM: Language Modeling based on Global Contexts via GNN
• NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
• Beyond Graph Neural Networks with Lifted Relational Neural Networks
• Learning Category Correlations for Multi-label Image Recognition with Graph Networks
• Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach
• CGNN: Traffic Classification with Graph Neural Network
• Automatic selection of clustering algorithms using supervised graph embedding
• Provably Powerful Graph Networks
• Zoom in to where it matters: a hierarchical graph based model for mammogram analysis
• A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting
• Omni-sourced Webly-supervised Learning for Video Recognition
• Node Injection for Class-specific Network Poisoning
• Person Re-identification with Deep Similarity-Guided Graph Neural Network
• End-to-End Entity Classification on Multimodal Knowledge Graphs
• Predicting cognitive scores with graph neural networks through sample selection learning
• DefenseVGAE: Defending against Adversarial Attacks on Graph Data via a Variational Graph Autoencoder
• AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting
• Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge
• Graph Convolutional Networks for Classification with a Structured Label Space
• Consensus-Aware Visual-Semantic Embedding for Image-Text Matching
• Learned Low Precision Graph Neural Networks
• Link Prediction via Graph Attention Network
• Learning by Abstraction: The Neural State Machine
• Advancing GraphSAGE with A Data-Driven Node Sampling
• How hard is to distinguish graphs with graph neural networks?
• Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base
• GIKT: A Graph-based Interaction Model for Knowledge Tracing
• Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
• Egocentric Object Manipulation Graphs
• FPConv: Learning Local Flattening for Point Convolution
• GraFormer: Graph Convolution Transformer for 3D Pose Estimation
• Structure fusion based on graph convolutional networks for semi-supervised classification
• wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction
• Deep Learning Methods for Retinal Blood Vessel Segmentation: Evaluation on Images with Retinopathy of Prematurity
• Spatial Dual-Modality Graph Reasoning for Key Information Extraction
• PH-GCN: Person Re-identification with Part-based Hierarchical Graph Convolutional Network
• Stabilized Medical Image Attacks
• Class-wise Dynamic Graph Convolution for Semantic Segmentation
• Approximation Ratios of Graph Neural Networks for Combinatorial Problems
• Spatio-Temporal Deep Graph Infomax
• Set2Graph: Learning Graphs From Sets
• Semantic Flow for Fast and Accurate Scene Parsing
• Graph Neural Networks for User Identity Linkage
• A Survey on Bayesian Deep Learning
• A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs
• Message Passing Networks for Molecules with Tetrahedral Chirality
• Neural Diffusion Model for Microscopic Cascade Prediction
• Motif-Driven Contrastive Learning of Graph Representations
• Identification of Patterns in Cosmic-Ray Arrival Directions using Dynamic Graph Convolutional Neural Networks
• Evaluating Deep Graph Neural Networks
• Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks
• 3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics
• Hierarchical Matching and Reasoning for Multi-Query Image Retrieval
• Dual-view Molecule Pre-training
• Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation
• BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
• Geometric Transformers for Protein Interface Contact Prediction
• SWAG: Item Recommendations using Convolutions on Weighted Graphs
• BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation
• Evaluating Logical Generalization in Graph Neural Networks
• HetEmotionNet: Two-Stream Heterogeneous Graph Recurrent Neural Network for Multi-modal Emotion Recognition
• Optimized Skeleton-based Action Recognition via Sparsified Graph Regression
• Language-Inspired Relation Transfer for Few-shot Class-Incremental Learning
• Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
• DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
• Unifying local and non-local signal processing with graph CNNs
• Temporal Graph Modeling for Skeleton-based Action Recognition
• Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild
• USER: Unsupervised Structural Entropy-based Robust Graph Neural Network
• Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
• A Hybrid Graph Neural Network Approach for Detecting PHP Vulnerabilities
• Learning to Drop: Robust Graph Neural Network via Topological Denoising
• Uncertainty quantification of molecular property prediction with Bayesian neural networks
• Graph Neural Networks for Motion Planning
• Named Entity Disambiguation using Deep Learning on Graphs
• Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization
• Graph Neural Networks for IceCube Signal Classification
• Bayesian Spatio-Temporal Graph Convolutional Network for Traffic Forecasting
• TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services
• Orthogonal Inductive Matrix Completion
• Multi-Label Classification with Label Graph Superimposing
• Graph Neural Network for Interpreting Task-fMRI Biomarkers
• SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection
• Deformable Filter Convolution for Point Cloud Reasoning
• Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties
• HONE: Higher-Order Network Embeddings
• Human-centric Spatio-Temporal Video Grounding With Visual Transformers
• Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction
• Discrete Signal Processing with Set Functions
• Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation
• Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization
• Directed Acyclic Graph Network for Conversational Emotion Recognition
• A Hybrid Similarity-Aware Graph Neural Network with Transformer for Node Classification
• GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps
• Relating Graph Neural Networks to Structural Causal Models
• Learning Cross-Domain Representation with Multi-Graph Neural Network
• Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning
• Towards More Practical Adversarial Attacks on Graph Neural Networks
• Counterfactual Learning on Graphs: A Survey
• HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing
• Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder
• RPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-Training
• Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks
• Inverse Design of a Graphene-Based Quantum Transducer via Neuroevolution
• Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning
• GIN: Graph-based Interaction-aware Constraint Policy Optimization for Autonomous Driving
• Solving Statistical Mechanics on Sparse Graphs with Feedback Set Variational Autoregressive Networks
• RigNet: Neural Rigging for Articulated Characters
• Balancing Multi-level Interactions for Session-based Recommendation
• Node Similarity Preserving Graph Convolutional Networks
• FSCNMF: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
• Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures
• A Probabilistic Framework for Location Inference from Social Media
• Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization
• Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
• Quantifying Classification Uncertainty using Regularized Evidential Neural Networks
• Objective Class-based Micro-Expression Recognition through Simultaneous Action Unit Detection and Feature Aggregation
• Visual Relationship Detection using Scene Graphs: A Survey
• Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
• Similarity Learning with Higher-Order Graph Convolutions for Brain Network Analysis
• Graph Coarsening with Neural Networks
• A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
• Node Embeddings and Exact Low-Rank Representations of Complex Networks
• Time-aware Gradient Attack on Dynamic Network Link Prediction
• Deep Graph Neural Networks with Shallow Subgraph Samplers
• GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
• Meta-Learning with Graph Neural Networks: Methods and Applications
• NODE-SELECT: A Graph Neural Network Based On A Selective Propagation Technique
• Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
• Deep Patent Landscaping Model Using Transformer and Graph Embedding
• Understanding Graph Neural Networks from Graph Signal Denoising Perspectives
• Hierarchical Opacity Propagation for Image Matting
• Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection
• Deep Graph Similarity Learning: A Survey
• SGAS: Sequential Greedy Architecture Search
• Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions
• Speaker attribution with voice profiles by graph-based semi-supervised learning
• A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video
• The Homophily Principle in Social Network Analysis
• Learning to simulate and design for structural engineering
• FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems
• GNN is a Counter? Revisiting GNN for Question Answering
• Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network
• SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
• Multi-dimensional Graph Convolutional Networks
• A Light Heterogeneous Graph Collaborative Filtering Model using Textual Information
• Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition
• Graph Deconvolutional Generation
• DCT and DST Filtering with Sparse Graph Operators
• Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review
• Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines
• Stability and Generalization of Graph Convolutional Neural Networks
• Neural Link Prediction with Walk Pooling
• Factor Graph Neural Network
• SPAGAN: Shortest Path Graph Attention Network
• Adversarial Classifier for Imbalanced Problems
• STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks
• Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
• A Spatio-Temporal Graph Convolutional Network for Gesture Recognition from High-Density Electromyography
• Temporal Graph Signal Decomposition
• AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers
• Leveraging Graph to Improve Abstractive Multi-Document Summarization
• Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation
• Recursive Graphical Neural Networks for Text Classification
• Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
• CoVA: Context-aware Visual Attention for Webpage Information Extraction
• Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic Graph
• Generative Graph Convolutional Network for Growing Graphs
• Online Planner Selection with Graph Neural Networks and Adaptive Scheduling
• Optimal Resource Allocation for Serverless Queries
• Discriminative structural graph classification
• Geometric Scattering Attention Networks
• Deep Hyperedges: a Framework for Transductive and Inductive Learning on Hypergraphs
• Real-time 3D Shape Instantiation for Partially-deployed Stent Segment from a Single 2D Fluoroscopic Image in Robot-assisted Fenestrated Endovascular Aortic Repair
• Graph neural network for 3D classification of ambiguities and optical crosstalk in scintillator-based neutrino detectors
• A Semi-Supervised Assessor of Neural Architectures
• Incorporating Biological Knowledge with Factor Graph Neural Network for Interpretable Deep Learning
• Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning
• Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
• Using Graph Neural Networks for Mass Spectrometry Prediction
• Interpretable Multi-Step Reasoning with Knowledge Extraction on Complex Healthcare Question Answering
• CasGCN: Predicting future cascade growth based on information diffusion graph
• LineMVGNN: Anti-Money Laundering with Line-Graph-Assisted Multi-View Graph Neural Networks
• Modeling Gate-Level Abstraction Hierarchy Using Graph Convolutional Neural Networks to Predict Functional De-Rating Factors
• edGNN: a Simple and Powerful GNN for Directed Labeled Graphs
• Scene Graph Reasoning for Visual Question Answering
• Learning K-way D-dimensional Discrete Code For Compact Embedding Representations
• CoarSAS2hvec: Heterogeneous Information Network Embedding with Balanced Network Sampling
• Android Malware Detection using Large-scale Network Representation Learning
• Graph Normalized-LMP Algorithm for Signal Estimation Under Impulsive Noise
• Hyperbolic Deep Neural Networks: A Survey
• PaStaNet: Toward Human Activity Knowledge Engine
• Graph Generative Models for Fast Detector Simulations in High Energy Physics
• Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of Nodes
• Dynamically Pruned Message Passing Networks for Large-Scale Knowledge Graph Reasoning
• Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
• DyGCN: Dynamic Graph Embedding with Graph Convolutional Network
• Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences
• Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks
• Socially-Aware Self-Supervised Tri-Training for Recommendation
• Link prediction in dynamic networks using random dot product graphs
• Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection
• Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction
• Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning
• Spatio-temporal Action Recognition: A Survey
• Frame Averaging for Invariant and Equivariant Network Design
• Self-supervised Graph Neural Networks without explicit negative sampling
• Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
• Tensor graph convolutional neural network
• GISNet: Graph-Based Information Sharing Network For Vehicle Trajectory Prediction
• Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks
• Finite-difference-informed graph network for solving steady-state incompressible flows on block-structured grids
• GraphConfRec: A Graph Neural Network-Based Conference Recommender System
• A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction
• Optimization of Graph Neural Networks with Natural Gradient Descent
• Few-Shot Image Classification via Contrastive Self-Supervised Learning
• General Partial Label Learning via Dual Bipartite Graph Autoencoder
• Towards Heterogeneous Multi-Agent Reinforcement Learning with Graph Neural Networks
• Directional Graph Networks
• Motion Guided 3D Pose Estimation from Videos
• Language Models as Emotional Classifiers for Textual Conversations
• mGNN: Generalizing the Graph Neural Networks to the Multilayer Case
• Adaptively Connected Neural Networks
• Linguistic Structure Guided Context Modeling for Referring Image Segmentation
• DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
• MER-GCN: Micro Expression Recognition Based on Relation Modeling with Graph Convolutional Network
• Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors
• HighlightMe: Detecting Highlights from Human-Centric Videos
• Learning Visual Commonsense for Robust Scene Graph Generation
• Knowledge-aware Contrastive Molecular Graph Learning
• On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions
• IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification
• Efficient long-distance relation extraction with DG-SpanBERT
• Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
• AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing
• Building Footprint Extraction with Graph Convolutional Network
• Associative Partial Domain Adaptation
• Pileup mitigation at the Large Hadron Collider with Graph Neural Networks
• Redundancy-Free Computation Graphs for Graph Neural Networks
• Simulation and Augmentation of Social Networks for Building Deep Learning Models
• Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning
• AutoMate: A Dataset and Learning Approach for Automatic Mating of CAD Assemblies
• A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
• Graph Convolutional Networks with EigenPooling
• From Local Structures to Size Generalization in Graph Neural Networks
• Towards Similarity Graphs Constructed by Deep Reinforcement Learning
• SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
• Short-Term Electricity Price Forecasting based on Graph Convolution Network and Attention Mechanism
• SCE: Scalable Network Embedding from Sparsest Cut
• Data Considerations in Graph Representation Learning for Supply Chain Networks
• Graph Representation Learning via Multi-task Knowledge Distillation
• Learning Graph While Training: An Evolving Graph Convolutional Neural Network
• CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network
• Graph Signal Processing for Geometric Data and Beyond: Theory and Applications
• Learning Deep Matrix Representations
• SRINet: Learning Strictly Rotation-Invariant Representations for Point Cloud Classification and Segmentation
• Edge Dithering for Robust Adaptive Graph Convolutional Networks
• Progressive Correspondence Pruning by Consensus Learning
• Robust Line Segments Matching via Graph Convolution Networks
• MAAS: Multi-modal Assignation for Active Speaker Detection
• Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
• Hierarchical Text Classification As Sub-Hierarchy Sequence Generation
• Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos
• On Graph Neural Networks versus Graph-Augmented MLPs
• All Graphs Lead to Rome: Learning Geometric and Cycle-Consistent Representations with Graph Convolutional Networks
• ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks
• Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
• Zero-Shot Semantic Segmentation
• Context-Aware Visual Compatibility Prediction
• Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
• Temporal Contrastive Graph Learning for Video Action Recognition and Retrieval
• Learning Edge Properties in Graphs from Path Aggregations
• Room Classification on Floor Plan Graphs using Graph Neural Networks
• Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction
• Label-guided Learning for Text Classification
• Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition
• HAWK: Rapid Android Malware Detection through Heterogeneous Graph Attention Networks
• Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
• Relation Modeling in Spatio-Temporal Action Localization
• Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs
• Outlier Aware Network Embedding for Attributed Networks
• Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction
• Simplicial Complex Representation Learning
• Learning Color Compatibility in Fashion Outfits
• Learning Topological Representation for Networks via Hierarchical Sampling
• Trimmed Action Recognition, Dense-Captioning Events in Videos, and Spatio-temporal Action Localization with Focus on ActivityNet Challenge 2019
• Session-based Social and Dependency-aware Software Recommendation
• Bidirectional Graph Reasoning Network for Panoptic Segmentation
• Cross-media Structured Common Space for Multimedia Event Extraction
• Self-Supervised Learning for Semi-Supervised Temporal Action Proposal
• Molecule Property Prediction and Classification with Graph Hypernetworks
• Influence maximization in unknown social networks: Learning Policies for Effective Graph Sampling
• The Validation of Graph Model-Based, Gate Level Low-Dimensional Feature Data for Machine Learning Applications
• Mini-batch graphs for robust image classification
• AffinityNet: semi-supervised few-shot learning for disease type prediction
• Video Self-Stitching Graph Network for Temporal Action Localization
• Revisiting 2D Convolutional Neural Networks for Graph-based Applications
• Unsupervised Event Classification with Graphs on Classical and Photonic Quantum Computers
• Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification
• PREDATOR: Registration of 3D Point Clouds with Low Overlap
• Joint User Association and Power Allocation in Heterogeneous Ultra Dense Network via Semi-Supervised Representation Learning
• Scribble-based Weakly Supervised Deep Learning for Road Surface Extraction from Remote Sensing Images
• Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
• A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
• Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling
• Gromov-Wasserstein Factorization Models for Graph Clustering
• Learning a Proposal Classifier for Multiple Object Tracking
• GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference
• Robot Navigation in Crowds by Graph Convolutional Networks with Attention Learned from Human Gaze
• Identifying Autism Spectrum Disorder Based on Individual-Aware Down-Sampling and Multi-Modal Learning
• L${}^2$-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
• Contextual Heterogeneous Graph Network for Human-Object Interaction Detection
• Learning and Interpreting Multi-Multi-Instance Learning Networks
• Dual Pointer Network for Fast Extraction of Multiple Relations in a Sentence
• Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter
• The Impact of Global Structural Information in Graph Neural Networks Applications
• Mixed Pooling Multi-View Attention Autoencoder for Representation Learning in Healthcare
• Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework
• Network Embedding via Deep Prediction Model
• Multi-Component Graph Convolutional Collaborative Filtering
• Longitudinal Citation Prediction using Temporal Graph Neural Networks
• Grouping-matrix based Graph Pooling with Adaptive Number of Clusters
• Identifying Influential Brokers on Social Media from Social Network Structure
• Artificial Intelligence in Drug Discovery: Applications and Techniques
• Learning a Static Bug Finder from Data
• Neural IR Meets Graph Embedding: A Ranking Model for Product Search
• SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator
• Fake News Detection using Semi-Supervised Graph Convolutional Network
• Learning to Infer Unseen Single-/Multi-Attribute-Object Compositions with Graph Networks
• HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs
• Multi-Channel Graph Convolutional Networks
• I Know You'll Be Back: Interpretable New User Clustering and Churn Prediction on a Mobile Social Application
• MeshWalker: Deep Mesh Understanding by Random Walks
• Privacy Attacks on Network Embeddings
• Online Semi-Supervised Learning with Bandit Feedback
• Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery
• ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks
• Explainable, Stable, and Scalable Graph Convolutional Networks for Learning Graph Representation
• MEMO: A Deep Network for Flexible Combination of Episodic Memories
• DGTN: Dual-channel Graph Transition Network for Session-based Recommendation
• Graph Learning-Convolutional Networks
• GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification
• Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network
• Rethinking Graph Neural Architecture Search from Message-passing
• Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
• Learning Diverse Fashion Collocation by Neural Graph Filtering
• GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition
• Simplifying Architecture Search for Graph Neural Network
• Fiedler Regularization: Learning Neural Networks with Graph Sparsity
• SPINE: Structural Identity Preserved Inductive Network Embedding
• Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
• Graph2Seq: Scalable Learning Dynamics for Graphs
• DAGCN: Dual Attention Graph Convolutional Networks
• Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
• Simplifying Clustering with Graph Neural Networks
• Neural Sentence Ordering Based on Constraint Graphs
• Learning Large-scale Location Embedding From Human Mobility Trajectories with Graphs
• Adaptive Hierarchical Down-Sampling for Point Cloud Classification
• Mask-GVAE: Blind Denoising Graphs via Partition
• Cerberus: Attribute-based person re-identification using semantic IDs
• ES-CTC: A Deep Neuroevolution Model for Cooperative Intelligent Freeway Traffic Control
• Benchmarking Graph Neural Networks on Link Prediction
• Graph-Revised Convolutional Network
• Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks
• Self-supervised edge features for improved Graph Neural Network training
• OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds
• Homogeneous and Heterogeneous Relational Graph for Visible-infrared Person Re-identification
• GraphFM: Graph Factorization Machines for Feature Interaction Modeling
• Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey
• Jointly Modeling Aspect and Sentiment with Dynamic Heterogeneous Graph Neural Networks
• Recurrent Graph Syntax Encoder for Neural Machine Translation
• Network In Graph Neural Network
• Recapture as You Want
• Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
• A Hierarchy of Graph Neural Networks Based on Learnable Local Features
• Health Status Prediction with Local-Global Heterogeneous Behavior Graph
• Community Detection Graph Convolutional Network for Overlap-Aware Speaker Diarization
• Data Poisoning Attack against Knowledge Graph Embedding
• SF-GRASS: Solver-Free Graph Spectral Sparsification
• TGCN: Time Domain Graph Convolutional Network for Multiple Objects Tracking
• Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks
• E(n) Equivariant Normalizing Flows
• Bilinear Graph Networks for Visual Question Answering
• Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence
• Graph Neural Network Based VC Investment Success Prediction
• Price-aware Recommendation with Graph Convolutional Networks
• Learning through structure: towards deep neuromorphic knowledge graph embeddings
• Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks
• Modeling multi-scale data via a network of networks
• Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks
• Exploring the Hierarchy in Relation Labels for Scene Graph Generation
• Amortized Bethe Free Energy Minimization for Learning MRFs
• Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview
• EQG-RACE: Examination-Type Question Generation
• R-GSN: The Relation-based Graph Similar Network for Heterogeneous Graph
• Learning Individual Causal Effects from Networked Observational Data
• Bipartite Graph Embedding via Mutual Information Maximization
• ANAE: Learning Node Context Representation for Attributed Network Embedding
• Revisiting Decomposable Submodular Function Minimization with Incidence Relations
• Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters
• Topology and Content Co-Alignment Graph Convolutional Learning
• Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks
• SCGG: A Deep Structure-Conditioned Graph Generative Model
• Heterogeneous Graph Neural Networks for Malicious Account Detection
• Multi-task Learning over Graph Structures
• Utilising Graph Machine Learning within Drug Discovery and Development
• Conditional Text Generation for Harmonious Human-Machine Interaction
• Positional Encoder Graph Neural Networks for Geographic Data
• Graph-guided Architecture Search for Real-time Semantic Segmentation
• PuzzleNet: Scene Text Detection by Segment Context Graph Learning
• Net2: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation
• GraphAttacker: A General Multi-Task GraphAttack Framework
• Feature Propagation on Graph: A New Perspective to Graph Representation Learning
• MGRR-Net: Multi-level Graph Relational Reasoning Network for Facial Action Units Detection
• Learning in High-Dimensional Feature Spaces Using ANOVA-Based Fast Matrix-Vector Multiplication
• Exploring the Representational Power of Graph Autoencoder
• Fusion Graph Convolutional Networks
• Graph Representation learning for Audio & Music genre Classification
• A Survey on Deep Learning for Neuroimaging-based Brain Disorder Analysis
• Topological based classification using graph convolutional networks
• A contribution to Optimal Transport on incomparable spaces
• SQL-to-Text Generation with Graph-to-Sequence Model
• LCS Graph Kernel Based on Wasserstein Distance in Longest Common Subsequence Metric Space
• Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
• HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation
• EPNE: Evolutionary Pattern Preserving Network Embedding
• Natural Image Matting via Guided Contextual Attention
• Graph Signal Processing -- Part III: Machine Learning on Graphs, from Graph Topology to Applications
• Probabilistic Numeric Convolutional Neural Networks
• Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network
• Regional based query in graph active learning
• Multi-task Graph Convolutional Neural Network for Calcification Morphology and Distribution Analysis in Mammograms
• Modeling Attention Flow on Graphs
• The 1st Agriculture-Vision Challenge: Methods and Results
• GN-Transformer: Fusing Sequence and Graph Representation for Improved Code Summarization
• InstantEmbedding: Efficient Local Node Representations
• Heterogeneous Graph Matching Networks
• Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs
• Few-shot Network Anomaly Detection via Cross-network Meta-learning
• Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders
• A Queueing-Theoretic Framework for Vehicle Dispatching in Dynamic Car-Hailing [technical report]
• User Memory Reasoning for Conversational Recommendation
• DrivAer Transformer: A high-precision and fast prediction method for vehicle aerodynamic drag coefficient based on the DrivAerNet++ dataset
• Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis
• Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks
• Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction
• Point Clouds Learning with Attention-based Graph Convolution Networks
• Topology Aware Deep Learning for Wireless Network Optimization
• Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes
• Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense
• GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks
• Detecting and analyzing missing citations to published scientific entities
• Learning Multi-modal Information for Robust Light Field Depth Estimation
• Can GAN Learn Topological Features of a Graph?
• DNN-based Speaker Embedding Using Subjective Inter-speaker Similarity for Multi-speaker Modeling in Speech Synthesis
• Look Again at the Syntax: Relational Graph Convolutional Network for Gendered Ambiguous Pronoun Resolution
• Neural Message Passing for Multi-Label Classification
• Deep learning in bioinformatics: introduction, application, and perspective in big data era
• Semi-supervised Anomaly Detection on Attributed Graphs
• Segmented Graph-Bert for Graph Instance Modeling
• Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts
• Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions
• On the Interpretability and Evaluation of Graph Representation Learning
• StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
• Spatial-Temporal Block and LSTM Network for Pedestrian Trajectories Prediction
• Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
• Graph Neural Network Architecture Search for Molecular Property Prediction
• JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image
• A framework for constructing a huge name disambiguation dataset: algorithms, visualization and human collaboration
• Policy-GNN: Aggregation Optimization for Graph Neural Networks
• Signal processing on simplicial complexes
• DeepHunter: A Graph Neural Network Based Approach for Robust Cyber Threat Hunting
• Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance
• Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation
• Pose-GNN : Camera Pose Estimation System Using Graph Neural Networks
• Graph Embedding for Recommendation against Attribute Inference Attacks
• A pipeline for fair comparison of graph neural networks in node classification tasks
• Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos
• Self-supervised Graph Representation Learning via Bootstrapping
• ASFGNN: Automated Separated-Federated Graph Neural Network
• PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction
• Video-based Facial Expression Recognition using Graph Convolutional Networks
• VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
• High-resolution rainfall-runoff modeling using graph neural network
• Why Propagate Alone? Parallel Use of Labels and Features on Graphs
• Multiplex Graph Networks for Multimodal Brain Network Analysis
• MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation
• GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily
• On an application of graph neural networks in population based SHM
• One-shot Scene Graph Generation
• Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection
• DySuse: Susceptibility Estimation in Dynamic Social Networks
• Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks
• Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks
• Understanding Concepts in Graph Signal Processing for Neurophysiological Signal Analysis
• A Graph-Based Context-Aware Model to Understand Online Conversations
• GENNAPE: Towards Generalized Neural Architecture Performance Estimators
• Relation-aware Video Reading Comprehension for Temporal Language Grounding
• PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds
• Enabling Automated FPGA Accelerator Optimization Using Graph Neural Networks
• Deep Attention-guided Graph Clustering with Dual Self-supervision
• AirObject: A Temporally Evolving Graph Embedding for Object Identification
• Label-Wise Graph Convolutional Network for Heterophilic Graphs
• Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
• PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery
• Missing Data Estimation in Temporal Multilayer Position-aware Graph Neural Network (TMP-GNN)
• An Overview on the Application of Graph Neural Networks in Wireless Networks
• Primitive Representation Learning for Scene Text Recognition
• Unsupervised Deep Manifold Attributed Graph Embedding
• GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
• Adversarial Graph Disentanglement
• VLG-Net: Video-Language Graph Matching Network for Video Grounding
• Metapath- and Entity-aware Graph Neural Network for Recommendation
• Graph Convolution with Low-rank Learnable Local Filters
• Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
• DeepGG: a Deep Graph Generator
• Compositional Video Synthesis with Action Graphs
• Relation Transformer Network
• Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction
• A Neural Rendering Framework for Free-Viewpoint Relighting
• Fundamental Limits of Deep Graph Convolutional Networks
• WSLLN: Weakly Supervised Natural Language Localization Networks
• Learning Functions over Sets via Permutation Adversarial Networks
• Generalizable Adversarial Attacks with Latent Variable Perturbation Modelling
• Recurrent Multi-Graph Neural Networks for Travel Cost Prediction
• Attentional Multilabel Learning over Graphs: A Message Passing Approach
• Semi-Supervised Learning on Graphs Based on Local Label Distributions
• Video Salient Object Detection via Adaptive Local-Global Refinement
• Neural Deepfake Detection with Factual Structure of Text
• Adaptive Serverless Learning
• A Survey on Neural-symbolic Learning Systems
• Equivariant Entity-Relationship Networks
• PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images
• Every Corporation Owns Its Structure: Corporate Credit Ratings via Graph Neural Networks
• ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation
• Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
• Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition
• Semi-Supervised Learning with Declaratively Specified Entropy Constraints
• A comprehensive study on the prediction reliability of graph neural networks for virtual screening
• CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning
• Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing
• Representation Learning for Heterogeneous Information Networks via Embedding Events
• Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
• Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks
• DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data
• Covid-19 Detection from Chest X-ray and Patient Metadata using Graph Convolutional Neural Networks
• A Targeted Universal Attack on Graph Convolutional Network
• Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware Detection
• Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness
• Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning
• Fusion with Hierarchical Graphs for Mulitmodal Emotion Recognition
• A benchmark study on reliable molecular supervised learning via Bayesian learning
• Modularity Optimization as a Training Criterion for Graph Neural Networks
• AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification
• Structure-Enhanced Meta-Learning For Few-Shot Graph Classification
• Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation
• Permutohedral-GCN: Graph Convolutional Networks with Global Attention
• Orthogonal Over-Parameterized Training
• Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification
• Point Cloud Audio Processing
• Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
• Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification
• AdarGCN: Adaptive Aggregation GCN for Few-Shot Learning
• Next Waves in Veridical Network Embedding
• Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning
• Dynamic Graph Representation for Partially Occluded Biometrics
• Graph Neural Lasso for Dynamic Network Regression
• Full-Body Motion Reconstruction with Sparse Sensing from Graph Perspective
• DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's disease
• Spectral Temporal Graph Neural Network for Trajectory Prediction
• Neural Collaborative Graph Machines for Table Structure Recognition
• Molecular Dynamics and Machine Learning Unlock Possibilities in Beauty Design -- A Perspective
• Feature Interaction-aware Graph Neural Networks
• Self-Constructing Graph Convolutional Networks for Semantic Labeling
• GCNScheduler: Scheduling Distributed Computing Applications using Graph Convolutional Networks
• Scalable Attack on Graph Data by Injecting Vicious Nodes
• Wasserstein Embedding for Graph Learning
• GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search
• GACAN: Graph Attention-Convolution-Attention Networks for Traffic Forecasting Based on Multi-granularity Time Series
• JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
• Graph Sequential Network for Reasoning over Sequences
• View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums
• LookHops: light multi-order convolution and pooling for graph classification
• HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM
• Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification
• Subjective Bias in Abstractive Summarization
• Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer
• LayoutGMN: Neural Graph Matching for Structural Layout Similarity
• Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network
• Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks
• Generalization bounds for graph convolutional neural networks via Rademacher complexity
• Domain Adaptative Causality Encoder
• Interpretable Stability Bounds for Spectral Graph Filters
• Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks
• Multi-Label Graph Convolutional Network Representation Learning
• Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning
• Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks
• Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints
• Contour Transformer Network for One-shot Segmentation of Anatomical Structures
• EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
• Discovering alignment relations with Graph Convolutional Networks: a biomedical case study
• Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
• Denoising User-aware Memory Network for Recommendation
• Node Copying: A Random Graph Model for Effective Graph Sampling
• Inferring Javascript types using Graph Neural Networks
• JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms
• PK-GCN: Prior Knowledge Assisted Image Classification using Graph Convolution Networks
• G2DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification
• Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning
• BotGraph: Web Bot Detection Based on Sitemap
• Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition
• AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement Learning
• Gauss-Newton Unrolled Neural Networks and Data-driven Priors for Regularized PSSE with Robustness
• Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability
• Graph Neural Processes: Towards Bayesian Graph Neural Networks
• Line Graph Neural Networks for Link Prediction
• Spectral Graph Convolutions for Population-based Disease Prediction
• Image Retrieval for Structure-from-Motion via Graph Convolutional Network
• Optimizing Large-Scale Fleet Management on a Road Network using Multi-Agent Deep Reinforcement Learning with Graph Neural Network
• TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
• GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
• RiskOracle: A Minute-level Citywide Traffic Accident Forecasting Framework
• Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
• New Ideas and Trends in Deep Multimodal Content Understanding: A Review
• Deep learning reveals hidden interactions in complex systems
• Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
• Building Segmentation through a Gated Graph Convolutional Neural Network with Deep Structured Feature Embedding
• Exploring The Spatial Reasoning Ability of Neural Models in Human IQ Tests
• HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Network
• Graph Attention Collaborative Similarity Embedding for Recommender System
• Neural Execution of Graph Algorithms
• An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation
• Modeling Human Mental States with an Entity-based Narrative Graph
• A Survey on Deep Geometry Learning: From a Representation Perspective
• Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
• BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices
• scGNN: scRNA-seq Dropout Imputation via Induced Hierarchical Cell Similarity Graph
• Simulating Execution Time of Tensor Programs using Graph Neural Networks
• Multi-Instance Learning by Utilizing Structural Relationship among Instances
• Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge
• CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendation
• Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations
• Towards a predictive spatio-temporal representation of brain data
• TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition
• GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory Prediction
• PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
• Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation
• Using Graph Neural Networks to model the performance of Deep Neural Networks
• Representation Learning of Graphs Using Graph Convolutional Multilayer Networks Based on Motifs
• Virtual Adversarial Training on Graph Convolutional Networks in Node Classification
• Network Diffusions via Neural Mean-Field Dynamics
• Topological based classification of paper domains using graph convolutional networks
• Real-Time Forecasting of Dockless Scooter-Sharing Demand: A Spatio-Temporal Multi-Graph Transformer Approach
• MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks
• Graph Ordering: Towards the Optimal by Learning
• Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs
• Graph Neural Distance Metric Learning with Graph-Bert
• Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach
• Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors
• CPR-GCN: Conditional Partial-Residual Graph Convolutional Network in Automated Anatomical Labeling of Coronary Arteries
• Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection
• Graph Embedding Based Hybrid Social Recommendation System
• Breaking the Expressive Bottlenecks of Graph Neural Networks
• Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
• Heterogeneous Hypergraph Embedding for Graph Classification
• Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases
• Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
• Partial Graph Reasoning for Neural Network Regularization
• Expanding Label Sets for Graph Convolutional Networks
• Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning
• Combating Disinformation in a Social Media Age
• The Convolution Exponential and Generalized Sylvester Flows
• Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder
• Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction
• Devil's in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification
• Learning Hierarchical Review Graph Representations for Recommendation
• Graph Neural Networks Including Sparse Interpretability
• GraLSP: Graph Neural Networks with Local Structural Patterns
• Dual-Attention Graph Convolutional Network
• Merchant Category Identification Using Credit Card Transactions
• Learning Depthwise Separable Graph Convolution from Data Manifold
• On Self-Distilling Graph Neural Network
• Deep Belief Network based representation learning for lncRNA-disease association prediction
• Decision Support for Intoxication Prediction Using Graph Convolutional Networks
• Multi-Scale Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition
• A Flexible Convolutional Solver with Application to Photorealistic Style Transfer
• Learning Invariant Representations of Social Media Users
• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
• Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification
• Inferring Multiple Relationships between ASes using Graph Convolutional Network
• Non-Overlapping Placement of Macro Cells based on Reinforcement Learning in Chip Design
• Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
• Quantum Graph Convolutional Neural Networks
• Regularizing Neural Networks via Minimizing Hyperspherical Energy
• ORD: Object Relationship Discovery for Visual Dialogue Generation
• Referring Image Segmentation via Cross-Modal Progressive Comprehension
• AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attention
• Detecting Hostile Posts using Relational Graph Convolutional Network
• Local, global and scale-dependent node roles
• Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Play
• Visual-Semantic Embedding Model Informed by Structured Knowledge
• Can Action be Imitated? Learn to Reconstruct and Transfer Human Dynamics from Videos
• An In-depth Summary of Recent Artificial Intelligence Applications in Drug Design
• Action Unit Detection with Joint Adaptive Attention and Graph Relation
• Quantum Walk Inspired Neural Networks for Graph-Structured Data
• Beyond Homophily with Graph Echo State Networks
• Lossless Compression of Structured Convolutional Models via Lifting
• Continuous-Depth Neural Models for Dynamic Graph Prediction
• Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network
• A Prior Guided Adversarial Representation Learning and Hypergraph Perceptual Network for Predicting Abnormal Connections of Alzheimer's Disease
• Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph
• CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
• Res-GCNN: A Lightweight Residual Graph Convolutional Neural Networks for Human Trajectory Forecasting
• Novel diffusion-derived distance measures for graphs
• Graph Representation Learning via Hard and Channel-Wise Attention Networks
• Efficient Transfer Bayesian Optimization with Auxiliary Information
• Stacked Graph Filter
• Quadratic GCN for Graph Classification
• Semantic data discovery from Social Big Data
• Recurrent Attention Walk for Semi-supervised Classification
• Graph Attribute Aggregation Network with Progressive Margin Folding
• Landmark2Vec: An Unsupervised Neural Network-Based Landmark Positioning Method
• Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes
• Relational Learning for Skill Preconditions
• Data-driven Policy on Feasibility Determination for the Train Shunting Problem
• Beyond Statistical Relations: Integrating Knowledge Relations into Style Correlations for Multi-Label Music Style Classification
• Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction
• Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
• Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification
• Deep learning of material transport in complex neurite networks
• Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks
• STD-Net: Structure-preserving and Topology-adaptive Deformation Network for 3D Reconstruction from a Single Image
• Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis
• Active Screening for Recurrent Diseases: A Reinforcement Learning Approach
• Skeleton-based Hand-Gesture Recognition with Lightweight Graph Convolutional Networks
• Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features
• Coarse-grained decomposition and fine-grained interaction for multi-hop question answering
• Learning the Implicit Semantic Representation on Graph-Structured Data
• Learning physics confers pose-sensitivity in structure-based virtual screening
• Generalized Embedding Machines for Recommender Systems
• Drug Package Recommendation via Interaction-aware Graph Induction
• SaaS: Speed as a Supervisor for Semi-supervised Learning
• Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems
• Towards Entity Alignment in the Open World: An Unsupervised Approach
• LEReg: Empower Graph Neural Networks with Local Energy Regularization
• AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud Processing
• Embedding Graphs on Grassmann Manifold
• ast2vec: Utilizing Recursive Neural Encodings of Python Programs
• InsertGNN: Can Graph Neural Networks Outperform Humans in TOEFL Sentence Insertion Problem?
• Hypergraph Pre-training with Graph Neural Networks
• SPA-GCN: Efficient and Flexible GCN Accelerator with an Application for Graph Similarity Computation
• Tackling the Local Bias in Federated Graph Learning
• A Comparative Study on Basic Elements of Deep Learning Models for Spatial-Temporal Traffic Forecasting
• Spotting insects from satellites: modeling the presence of Culicoides imicola through Deep CNNs
• Holistic 3D Scene Understanding from a Single Image with Implicit Representation
• GmCN: Graph Mask Convolutional Network
• Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism
• An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms
• On the combination of graph data for assessing thin-file borrowers' creditworthiness
• Classifying the Cosmic-Ray Proton and Light Groups on the LHAASO-KM2A Experiment with the Graph Neural Network
• Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition
• Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification
• Message Passing in Graph Convolution Networks via Adaptive Filter Banks
• Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering
• A Unified Deep Learning Formalism For Processing Graph Signals
• Uncertainty quantification of molecular property prediction using Bayesian neural network models
• Reliable Graph Neural Network Explanations Through Adversarial Training
• Revelio: ML-Generated Debugging Queries for Distributed Systems
• Scalable Graph Neural Network-based framework for identifying critical nodes and links in Complex Networks
• Finding Appropriate Traffic Regulations via Graph Convolutional Networks
• Learning Primal Heuristics for Mixed Integer Programs
• Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension
• Multimodal Deep Network Embedding with Integrated Structure and Attribute Information
• Multi-Modal Retrieval using Graph Neural Networks
• Matrix Completion via Factorizing Polynomials
• Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop
• Learning Hierarchical Graph Neural Networks for Image Clustering
• A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction
• Relational Graph Neural Networks for Fraud Detection in a Super-App environment
• Graph Convolution Networks Using Message Passing and Multi-Source Similarity Features for Predicting circRNA-Disease Association
• Neuralizing Efficient Higher-order Belief Propagation
• Structure-Aware Label Smoothing for Graph Neural Networks
• Deep Generative Modeling in Network Science with Applications to Public Policy Research
• Instance-Aware Graph Convolutional Network for Multi-Label Classification
• A Graph Representation of Semi-structured Data for Web Question Answering
• A Framework for Joint Unsupervised Learning of Cluster-Aware Embedding for Heterogeneous Networks
• Generating superpixels using deep image representations
• PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation
• HENIN: Learning Heterogeneous Neural Interaction Networks for Explainable Cyberbullying Detection on Social Media
• HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation
• Progressive Representative Labeling for Deep Semi-Supervised Learning
• AdaGNN: A multi-modal latent representation meta-learner for GNNs based on AdaBoosting
• Data-Driven Learning of Geometric Scattering Networks
• Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
• Machine Learning Applications for Therapeutic Tasks with Genomics Data
• Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge
• Planted Dense Subgraphs in Dense Random Graphs Can Be Recovered using Graph-based Machine Learning
• Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
• Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks
• Tree-Constrained Graph Neural Networks For Argument Mining
• Robust Hierarchical Graph Classification with Subgraph Attention
• CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
• TagPick: A System for Bridging Micro-Video Hashtags and E-commerce Categories
• On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks
• Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy
• Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data
• PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction
• GraphITE: Estimating Individual Effects of Graph-structured Treatments
• Graph Attention Multi-Agent Fleet Autonomy for Advanced Air Mobility
• Distributed Community Detection for Large Scale Networks Using Stochastic Block Model
• HeMI: Multi-view Embedding in Heterogeneous Graphs
• Hybrid Dynamic-static Context-aware Attention Network for Action Assessment in Long Videos
• Signed Graph Attention Networks
• Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
• Directed hypergraph neural network
• Adaptive Neural Message Passing for Inductive Learning on Hypergraphs
• Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction
• Why Do We Click: Visual Impression-aware News Recommendation
• Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)
• Alternating ConvLSTM: Learning Force Propagation with Alternate State Updates
• Hop Sampling: A Simple Regularized Graph Learning for Non-Stationary Environments
• NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
• Enriching language models with graph-based context information to better understand textual data
• Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation
• Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture
• CityNet: A Comprehensive Multi-Modal Urban Dataset for Advanced Research in Urban Computing
• Partial Domain Adaptation Using Graph Convolutional Networks
• Graph Neural Networks with Composite Kernels
• Low-Rank Matrix Completion: A Contemporary Survey
• Benchmark Tests of Convolutional Neural Network and Graph Convolutional Network on HorovodRunner Enabled Spark Clusters
• All-In-One: Artificial Association Neural Networks
• Semi-supervised Learning with Adaptive Neighborhood Graph Propagation Network
• Hybrid Low-order and Higher-order Graph Convolutional Networks
• Explainable Video Action Reasoning via Prior Knowledge and State Transitions
• Geometrically Principled Connections in Graph Neural Networks
• Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph
• A Quotient Space Formulation for Generative Statistical Analysis of Graphical Data
• Inferring halo masses with Graph Neural Networks
• Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions
• Unsupervised Geometric Disentanglement for Surfaces via CFAN-VAE
• Enterprise Analytics using Graph Database and Graph-based Deep Learning
• Trajectory Prediction with Graph-based Dual-scale Context Fusion
• Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs
• CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations
• Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks
• Monocular Human Shape and Pose with Dense Mesh-borne Local Image Features
• GraSSNet: Graph Soft Sensing Neural Networks
• Generating Unrestricted 3D Adversarial Point Clouds
• Robust Dynamic Network Embedding via Ensembles
• Graph Self-Supervised Learning with Learnable Structural and Positional Encodings
• A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts
• A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations
• GIPA: A General Information Propagation Algorithm for Graph Learning
• GrabQC: Graph based Query Contextualization for automated ICD coding
• Cross-Modal Progressive Comprehension for Referring Segmentation
• Multi-Aspect Temporal Network Embedding: A Mixture of Hawkes Process View
• Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution
• Neural Consciousness Flow
• Human-centric Relation Segmentation: Dataset and Solution
• Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies
• Jet characterization in Heavy Ion Collisions by QCD-Aware Graph Neural Networks
• Estimating Fund-Raising Performance for Start-up Projects from a Market Graph Perspective
• Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities
• Resilient UAV Swarm Communications with Graph Convolutional Neural Network
• Noise-robust classification with hypergraph neural network
• Heterogeneous Graph based Deep Learning for Biomedical Network Link Prediction
• Quantifying Uncertainty in Deep Spatiotemporal Forecasting
• Graph Neural Networks for Learning Real-Time Prices in Electricity Market
• Trainable Class Prototypes for Few-Shot Learning
• ConvDySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention and Convolutional Neural Networks
• Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline
• Deep Image Synthesis from Intuitive User Input: A Review and Perspectives
• Dual Geometric Graph Network (DG2N) -- Iterative network for deformable shape alignment
• Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis
• Stronger Transformers for Neural Multi-Hop Question Generation
• PSTN: Periodic Spatial-temporal Deep Neural Network for Traffic Condition Prediction
• USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems
• Deep Neural Network for DrawiNg Networks, (DNN)^2
• Jointly Learnable Data Augmentations for Self-Supervised GNNs
• Temporal Graph Network Embedding with Causal Anonymous Walks Representations
• DC-GNet: Deep Mesh Relation Capturing Graph Convolution Network for 3D Human Shape Reconstruction
• Parallel Multi-Graph Convolution Network For Metro Passenger Volume Prediction
• Progressive Cluster Purification for Transductive Few-shot Learning
• Multiscale Laplacian Learning
• Probabilistic modeling of lake surface water temperature using a Bayesian spatio-temporal graph convolutional neural network
• Learning the Markov Decision Process in the Sparse Gaussian Elimination
• Inductive learning for product assortment graph completion
• MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning
• Heterogeneous Stream-reservoir Graph Networks with Data Assimilation
• GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs
• Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings
• Simple Baseline for Single Human Motion Forecasting
• Compositional Structure Learning for Sequential Video Data
• Equivariant and Invariant Reynolds Networks
• BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network
• LSTA-Net: Long short-term Spatio-Temporal Aggregation Network for Skeleton-based Action Recognition
• LW-GCN: A Lightweight FPGA-based Graph Convolutional Network Accelerator
• Inferential SIR-GN: Scalable Graph Representation Learning
• Financial ticket intelligent recognition system based on deep learning
• GAIN: Graph Attention & Interaction Network for Inductive Semi-Supervised Learning over Large-scale Graphs
• Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation
• Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration
• Efficient Sampling for Predictor-Based Neural Architecture Search
• Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks
• Drug-disease Graph: Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data
• Semi-Supervised Cervical Dysplasia Classification With Learnable Graph Convolutional Network
• Deep learning architectures for inference of AC-OPF solutions
• Temporal Network Representation Learning via Historical Neighborhoods Aggregation
• Flow-based Generative Models for Learning Manifold to Manifold Mappings
• Analyzing the Performance of Graph Neural Networks with Pipe Parallelism
• Competition analysis on the over-the-counter credit default swap market
• DeepStrip: High Resolution Boundary Refinement
• GeoGraph: Learning graph-based multi-view object detection with geometric cues end-to-end
• Pair-view Unsupervised Graph Representation Learning
• Dual Temporal Memory Network for Efficient Video Object Segmentation
• Particle Track Reconstruction using Geometric Deep Learning
• Global Context Networks
• Representation Learning of Reconstructed Graphs Using Random Walk Graph Convolutional Network
• UCNN: A Convolutional Strategy on Unstructured Mesh
• Unsupervised Hierarchical Graph Representation Learning by Mutual Information Maximization
• Does a Hybrid Neural Network based Feature Selection Model Improve Text Classification?
• Knowledge Grounded Conversational Symptom Detection with Graph Memory Networks
• Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis
• Stochastic encoding of graphs in deep learning allows for complex analysis of gender classification in resting-state and task functional brain networks from the UK Biobank
• Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine Learning on Graphs with Applications to Modeling of Cytoskeleton
• Predicting Nanorobot Shapes via Generative Models
• Out-of-Town Recommendation with Travel Intention Modeling
• Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models
• DeepWalking Backwards: From Embeddings Back to Graphs
• Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification
• Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
• Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning
• Group-Connected Multilayer Perceptron Networks
• Collective Entity Alignment via Adaptive Features
• Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification
• DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction
• Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration
• Larger-Context Tagging: When and Why Does It Work?
• A Deep Emulator for Secondary Motion of 3D Characters
• Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification
• Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms
• Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction
• Lorentzian Graph Convolutional Networks
• Context-Aware Graph Attention Networks
• Into the Battlefield: Quantifying and Modeling Intra-community Conflicts in Online Discussion
• HiCoRe: Visual Hierarchical Context-Reasoning
• Social Influence Prediction with Train and Test Time Augmentation for Graph Neural Networks
• TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning
• In-Machine-Learning Database: Reimagining Deep Learning with Old-School SQL
• Personalized Hashtag Recommendation for Micro-videos
• Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN
• Adversarial Learning for Supervised and Semi-supervised Relation Extraction in Biomedical Literature
• Neural Stochastic Block Model & Scalable Community-Based Graph Learning
• Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning
• Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization
• Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks
• Out-of-Vocabulary Embedding Imputation with Grounded Language Information by Graph Convolutional Networks
• Learning Differential Diagnosis of Skin Conditions with Co-occurrence Supervision using Graph Convolutional Networks
• Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding
• Mutual Information Maximization in Graph Neural Networks
• Bot-Match: Social Bot Detection with Recursive Nearest Neighbors Search
• Node Embedding via Word Embedding for Network Community Discovery
• GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic Retinopathy
• TreeRNN: Topology-Preserving Deep GraphEmbedding and Learning
• Group Activity Prediction with Sequential Relational Anticipation Model
• Structure-Aware Human-Action Generation
• TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix
• A Visual Analytics Framework for Contrastive Network Analysis
• Balanced Order Batching with Task-Oriented Graph Clustering
• Few-Shot Object Detection via Knowledge Transfer
• Zero-Shot Human-Object Interaction Recognition via Affordance Graphs
• About Graph Degeneracy, Representation Learning and Scalability
• Graph Neural Network based Service Function Chaining for Automatic Network Control
• Learning Features of Network Structures Using Graphlets
• GINet: Graph Interaction Network for Scene Parsing
• Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification
• Towards Causal Explanation Detection with Pyramid Salient-Aware Network
• Framework for Designing Filters of Spectral Graph Convolutional Neural Networks in the Context of Regularization Theory
• Neural Topic Modeling by Incorporating Document Relationship Graph
• Overcoming Data Sparsity in Group Recommendation
• Fast Mesh Data Augmentation via Chebyshev Polynomial of Spectral filtering
• Set Aggregation Network as a Trainable Pooling Layer
• Learning Robust Representations with Graph Denoising Policy Network
• Dynamic Mode Decomposition based feature for Image Classification
• On Semi-Supervised Multiple Representation Behavior Learning
• Semantic Graph Convolutional Network for Implicit Discourse Relation Classification
• weg2vec: Event embedding for temporal networks
• Graph Convolutional Networks Meet with High Dimensionality Reduction
• Modelling Irregular Spatial Patterns using Graph Convolutional Neural Networks
• Learnable Pooling in Graph Convolution Networks for Brain Surface Analysis
• Spectral Network Embedding: A Fast and Scalable Method via Sparsity
• struc2gauss: Structural Role Preserving Network Embedding via Gaussian Embedding
• Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data
• The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version
• When Radiology Report Generation Meets Knowledge Graph
• Towards an Efficient and General Framework of Robust Training for Graph Neural Networks
• Advances in Collaborative Filtering and Ranking
• Towards information-rich, logical text generation with knowledge-enhanced neural models
• Graph Convolution for Multimodal Information Extraction from Visually Rich Documents
• Graph-Based Method for Anomaly Prediction in Brain Network
• Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization
• Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective
• Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs
• Automatic Text Extractive Summarization Based on Graph and Pre-trained Language Model Attention
• Graph Signal Processing over a Probability Space of Shift Operators
• AMMASurv: Asymmetrical Multi-Modal Attention for Accurate Survival Analysis with Whole Slide Images and Gene Expression Data
• NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
• EGC2: Enhanced Graph Classification with Easy Graph Compression
• DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction
• Comparison of Syntactic and Semantic Representations of Programs in Neural Embeddings
• A Semi-Supervised Approach for Automatic Crystal Structure Classification
• A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking
• Differentiable Representations For Multihop Inference Rules
• Towards Robust Reasoning over Knowledge Graphs
• Topology-Aware Hashing for Effective Control Flow Graph Similarity Analysis
• Consistent Multiple Sequence Decoding
• Generating an Overview Report over Many Documents
• Predicting Station-Level Bike-Sharing Demands Using Graph Convolutional Neural Network
• URIR: Recommendation algorithm of user RNN encoder and item encoder based on knowledge graph
• The CAT SET on the MAT: Cross Attention for Set Matching in Bipartite Hypergraphs
• Investigating Estimated Kolmogorov Complexity as a Means of Regularization for Link Prediction
• Differentially Private Link Prediction With Protected Connections
• FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity Mapping
• Patch Transformer for Multi-tagging Whole Slide Histopathology Images
• Exploration-Exploitation Motivated Variational Auto-Encoder for Recommender Systems
• Sensor selection on graphs via data-driven node sub-sampling in network time series
• Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos
• Fast Generating A Large Number of Gumbel-Max Variables
• MeronymNet: A Hierarchical Approach for Unified and Controllable Multi-Category Object Generation
• Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network
• Exploiting Transductive Property of Graph Convolutional Neural Networks with Less Labeling Effort
• SocialTrans: A Deep Sequential Model with Social Information for Web-Scale Recommendation Systems
• Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation
• NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset
• DRTS Parsing with Structure-Aware Encoding and Decoding
• Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation
• Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
• Deep Learning Meets SAR
• Transformer-based Dual Relation Graph for Multi-label Image Recognition
• Multiple Metric Learning for Structured Data
• Relevant Region Prediction for Crowd Counting
• Label-Aware Graph Convolutional Networks
• CoRGi: Content-Rich Graph Neural Networks with Attention
• Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
• Graph Neural Network for Hamiltonian-Based Material Property Prediction
• Deep graph learning for semi-supervised classification
• What's Wrong with the Bottom-up Methods in Arbitrary-shape Scene Text Detection
• Induction of Decision Trees based on Generalized Graph Queries
• StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis
• Embedded-Graph Theory
• Fast Haar Transforms for Graph Neural Networks
• DeepDrawing: A Deep Learning Approach to Graph Drawing
• Graph Representation Learning Network via Adaptive Sampling
• One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction
• Revisiting SVD to generate powerful Node Embeddings for Recommendation Systems
• Data-Driven Self-Supervised Graph Representation Learning
• Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion
• Semi-Supervised Deep Learning for Multiplex Networks
• RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs
• Equivariant Neural Network for Factor Graphs
• Edge but not Least: Cross-View Graph Pooling
• Context-aware Tree-based Deep Model for Recommender Systems
• Representation Learning for Short Text Clustering
• Grouping Search Results with Product Graphs in E-commerce Platforms
• Edge-similarity-aware Graph Neural Networks
• Improving Text-Independent Speaker Verification with Auxiliary Speakers Using Graph
• MIRA: Leveraging Multi-Intention Co-click Information in Web-scale Document Retrieval using Deep Neural Networks
• Node Copying for Protection Against Graph Neural Network Topology Attacks
• Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation
• IllumiNet: Transferring Illumination from Planar Surfaces to Virtual Objects in Augmented Reality
• Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach
• Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features
• Tesla-Rapture: A Lightweight Gesture Recognition System from mmWave Radar Point Clouds
• RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks
• Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework
• Can NetGAN be improved on short random walks?
• Evaluating Generalization and Transfer Capacity of Multi-Agent Reinforcement Learning Across Variable Number of Agents
• Graph Neural Network for Large-Scale Network Localization
• Training Graph Neural Networks by Graphon Estimation
• Learn to Propagate Reliably on Noisy Affinity Graphs
• A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning
• Edge-featured Graph Neural Architecture Search
• Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
• PotentialNet for Molecular Property Prediction
• An FEA surrogate model with Boundary Oriented Graph Embedding approach
• Saliency Prediction with External Knowledge
• Prior Signal Editing for Graph Filter Posterior Fairness Constraints
• Towards Self-Explainable Graph Neural Network
• Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search
• 3D Shapes Local Geometry Codes Learning with SDF
• GGP: A Graph-based Grouping Planner for Explicit Control of Long Text Generation
• Graph Wasserstein Correlation Analysis for Movie Retrieval
• Context Aware Object Geotagging
• Visualizing Semantic Structures of Sequential Data by Learning Temporal Dependencies
• NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications
• Beyond Language: Learning Commonsense from Images for Reasoning
• Multiple Graph Adversarial Learning
• Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain Connectivity
• Multi-Label Network Classification via Weighted Personalized Factorizations
• Multipath Graph Convolutional Neural Networks
• Meta-Active Learning for Node Response Prediction in Graphs
• Saliency-Associated Object Tracking
• Graph Convolutional Networks Reveal Neural Connections Encoding Prosthetic Sensation
• One-Shot Object Affordance Detection in the Wild
• Multi-Hot Compact Network Embedding
• Based on Graph-VAE Model to Predict Student's Score
• Decoupled Variational Embedding for Signed Directed Networks
• OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation
• Understanding Information Processing in Human Brain by Interpreting Machine Learning Models
• On Generalization of Graph Autoencoders with Adversarial Training
• Beyond Observed Connections : Link Injection
• Extrapolating paths with graph neural networks
• Scalar Coupling Constant Prediction Using Graph Embedding Local Attention Encoder
• Graph Feature Gating Networks
• Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks
• TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations
• Constrained Shortest Path Search with Graph Convolutional Neural Networks
• Rotation Equivariant 3D Hand Mesh Generation from a Single RGB Image
• Signed Bipartite Graph Neural Networks
• Spot What Matters: Learning Context Using Graph Convolutional Networks for Weakly-Supervised Action Detection
• On the Global Self-attention Mechanism for Graph Convolutional Networks
• Layer-stacked Attention for Heterogeneous Network Embedding
• Nominal Compound Chain Extraction: A New Task for Semantic-enriched Lexical Chain
• Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning
• 3D Meta Point Signature: Learning to Learn 3D Point Signature for 3D Dense Shape Correspondence
• Semantic Preserving Embeddings for Generalized Graphs
• NABU $-$ Multilingual Graph-based Neural RDF Verbalizer
• What Remains of Visual Semantic Embeddings
• Accelerating Metropolis-Hastings with Lightweight Inference Compilation
• On the Significance of Question Encoder Sequence Model in the Out-of-Distribution Performance in Visual Question Answering
• ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups
• Inferring Mesoscale Models of Neural Computation
• Graph Convolutional Network with Generalized Factorized Bilinear Aggregation
• Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice
• STR-GODEs: Spatial-Temporal-Ridership Graph ODEs for Metro Ridership Prediction
• A Unified Seeding Framework
• Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapes
• Convolutional Neural Network on Semi-Regular Triangulated Meshes and its Application to Brain Image Data
• Spectral clustering of annotated graphs using a factor graph representation
• GA Based Q-Attack on Community Detection
• Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions
• Arbitrary Style Transfer using Graph Instance Normalization
• DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations
• Curvature Graph Neural Network
• Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs
• Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classification
• Policy Message Passing: A New Algorithm for Probabilistic Graph Inference
• Exploring Correlations in Multiple Facial Attributes through Graph Attention Network
• Spread-gram: A spreading-activation schema of network structural learning
• Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution
• Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis
• Dynamic Joint Variational Graph Autoencoders
• Just-in-Time Dynamic-Batching
• TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network
• Named Entity Normalization Model Using Edge Weight Updating Neural Network: Assimilation Between Knowledge-Driven Graph and Data-Driven Graph
• HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions
• Graph Diffusion-Embedding Networks
• Enhancing Geometric Deep Learning via Graph Filter Deconvolution
• Survey of Image Based Graph Neural Networks
• Detecting intracranial aneurysm rupture from 3D surfaces using a novel GraphNet approach
• EEG-based video identification using graph signal modeling and graph convolutional neural network
• Cascading: Association Augmented Sequential Recommendation
• Timestamping Documents and Beliefs
• Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation
• Event Detection on Dynamic Graphs
• A Graph Neural Network Approach for Product Relationship Prediction
• Customized Graph Embedding: Tailoring Embedding Vectors to different Applications
• Network representation learning: A macro and micro view
• Linked Recurrent Neural Networks
• GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
• IGLU: Efficient GCN Training via Lazy Updates
• Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks
• Multi-modal Entity Alignment in Hyperbolic Space
• DyDiff-VAE: A Dynamic Variational Framework for Information Diffusion Prediction
• ${\ell }_2$-norm Flow Diffusion in Near-Linear Time
• DNA-GCN: Graph convolutional networks for predicting DNA-protein binding
• Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network
• LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs
• Formalizing Distribution Inference Risks
• Wall Stress Estimation of Cerebral Aneurysm based on Zernike Convolutional Neural Networks
• GenURL: A General Framework for Unsupervised Representation Learning
• Comparative Code Structure Analysis using Deep Learning for Performance Prediction
• Graph Classification Based on Skeleton and Component Features
• Edge-Labeling based Directed Gated Graph Network for Few-shot Learning
• Reinforced Contact Tracing and Epidemic Intervention
• Lookup subnet based Spatial Graph Convolutional neural Network
• Fractional order graph neural network
• MGA: Momentum Gradient Attack on Network
• Metaknowledge Extraction Based on Multi-Modal Documents
• Knowledge Generation -- Variational Bayes on Knowledge Graphs
• Parameter-Efficient Neural Question Answering Models via Graph-Enriched Document Representations
• A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
• NEMR: Network Embedding on Metric of Relation
• geoGAT: Graph Model Based on Attention Mechanism for Geographic Text Classification
• An End-to-End Framework for Cold Question Routing in Community Question Answering Services
• Dynamic Virtual Graph Significance Networks for Predicting Influenza
• Meta-Path-Free Representation Learning on Heterogeneous Networks
• Experiments with graph convolutional networks for solving the vertex $p$-center problem
• Variational Embeddings for Community Detection and Node Representation
• Modeling Global Semantics for Question Answering over Knowledge Bases
• Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification
• High Tension Lines: Predicting robustness of high-voltage power-grids to cascading failure using network embedding
• Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making
• Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graph
• A Collective Learning Framework to Boost GNN Expressiveness
• Relationship-based Neural Baby Talk
• GAHNE: Graph-Aggregated Heterogeneous Network Embedding
• Using Laplacian Spectrum as Graph Feature Representation
• Better Understanding Hierarchical Visual Relationship for Image Caption
• Knowledge as Invariance -- History and Perspectives of Knowledge-augmented Machine Learning
• A Multi-Modal Transformer-based Code Summarization Approach for Smart Contracts
• Modeling Heterogeneous Edges to Represent Networks with Graph Auto-Encoder
• DSSLP: A Distributed Framework for Semi-supervised Link Prediction
• Deep Graph Matching under Quadratic Constraint
• Interaction Graphs for Object Importance Estimation in On-road Driving Videos
• An Experimental Study of the Transferability of Spectral Graph Networks
• Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning
• Diversified Multiscale Graph Learning with Graph Self-Correction
• Deep graph embedding for prioritizing synergistic anticancer drug combinations
• Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection
• Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation
• Affinity Graph Supervision for Visual Recognition
• Structure-Aware Face Clustering on a Large-Scale Graph with $10^7$ Nodes
• Contextual Scene Augmentation and Synthesis via GSACNet
• Bipartite Link Prediction based on Topological Features via 2-hop Path
• Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph
• Bidirectional group random walk based network embedding for asymmetric proximity
• Learning Node Representations from Noisy Graph Structures
• Permutation-Invariant Subgraph Discovery
• Learning Equivariant Representations
• CARLS: Cross-platform Asynchronous Representation Learning System
• Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs
• Long Short-Term Relation Networks for Video Action Detection
• Complex network prediction using deep learning
• Estimating Early Fundraising Performance of Innovations via Graph-based Market Environment Model
• A Graph Convolutional Neural Network based Framework for Estimating Future Citations Count of Research Articles
• Distributed Cartesian Power Graph Segmentation for Graphon Estimation
• Personalized Bundle Recommendation in Online Games
• Adversarial Refinement Network for Human Motion Prediction
• VSGM -- Enhance robot task understanding ability through visual semantic graph
• Learn to Cluster Faces via Pairwise Classification
• Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases
• An Energy-Based View of Graph Neural Networks
• Measuring Quadrangle Formation in Complex Networks
• Gumbel-softmax Optimization: A Simple General Framework for Combinatorial Optimization Problems on Graphs
• Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition
• Geometric Brain Surface Network For Brain Cortical Parcellation
• GL-Coarsener: A Graph representation learning framework to construct coarse grid hierarchy for AMG solvers
• Lifelog Patterns Analyzation using Graph Embedding based on Deep Neural Network
• Robust Pedestrian Attribute Recognition Using Group Sparsity for Occlusion Videos
• Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning
• Convolutions for Spatial Interaction Modeling
• Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection
• Subgraph Signal Processing
• DeepWORD: A GCN-based Approach for Owner-Member Relationship Detection in Autonomous Driving
• Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks
• Deep Clustering with Measure Propagation
• Simplex Initialization: A Survey of Techniques and Trends
• GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
• Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation
• DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
• Pooling in Graph Convolutional Neural Networks
• Improving Expressivity of Graph Neural Networks
• Learning Large-Scale Topological Maps Using Sum-Product Networks