232 citations · 1.4k across the 72 of their papers we have counts for
73 papers
Driving behavior-guided battery health monitoring for electric vehicles using machine learning
Nanhua Jiang, Jiawei Zhang, Weiran Jiang +4
An accurate estimation of the state of health (SOH) of batteries is critical to ensuring the safe and reliable operation of electric vehicles (EVs). Feature-based machine learning…
Unsupervised Multi-document Summarization with Holistic Inference
Haopeng Zhang, Sangwoo Cho, Kaiqiang Song +4
Multi-document summarization aims to obtain core information from a collection of documents written on the same topic. This paper proposes a new holistic framework for unsupervised…
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
Siwei Zhang, Yun Xiong, Yao Zhang +3
Continuous-time dynamic graph modeling is a crucial task for many real-world applications, such as financial risk management and fraud detection. Though existing dynamic graph mode…
RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs
Zhouxia Wang, Jiawei Zhang, Tianshui Chen +2
Blind face restoration aims at recovering high-quality face images from those with unknown degradations. Current algorithms mainly introduce priors to complement high-quality detai…
Graph Collaborative Signals Denoising and Augmentation for Recommendation
Ziwei Fan, Ke Xu, Zhang Dong +3
Graph collaborative filtering (GCF) is a popular technique for capturing high-order collaborative signals in recommendation systems. However, GCF's bipartite adjacency matrix, whic…
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang +4
Since group activities have become very common in daily life, there is an urgent demand for generating recommendations for a group of users, referred to as group recommendation tas…
Measuring and Sampling: A Metric-guided Subgraph Learning Framework for Graph Neural Network
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
Graph neural network (GNN) has shown convincing performance in learning powerful node representations that preserve both node attributes and graph structural information. However,…
Translational Concept Embedding for Generalized Compositional Zero-shot Learning
He Huang, Wei Tang, Jiawei Zhang +1
Generalized compositional zero-shot learning means to learn composed concepts of attribute-object pairs in a zero-shot fashion, where a model is trained on a set of seen concepts a…
A Self-supervised Mixed-curvature Graph Neural Network
Li Sun, Zhongbao Zhang, Junda Ye +4
Graph representation learning received increasing attentions in recent years. Most of existing methods ignore the complexity of the graph structures and restrict graphs in a single…
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision
Zhilu Zhang, Haolin Wang, Ming Liu +3
Learning RAW-to-sRGB mapping has drawn increasing attention in recent years, wherein an input raw image is trained to imitate the target sRGB image captured by another camera. Howe…
Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization
Haopeng Zhang, Jiawei Zhang
Unsupervised document summarization has re-acquired lots of attention in recent years thanks to its simplicity and data independence. In this paper, we propose a graph-based unsupe…
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Li Sun, Zhongbao Zhang, Jiawei Zhang +4
Learning representations for graphs plays a critical role in a wide spectrum of downstream applications. In this paper, we summarize the limitations of the prior works in three fol…
Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection
Yuxiang Ren, Bo Wang, Jiawei Zhang +1
The explosive growth of fake news along with destructive effects on politics, economy, and public safety has increased the demand for fake news detection. Fake news on social media…
Label Contrastive Coding based Graph Neural Network for Graph Classification
Yuxiang Ren, Jiyang Bai, Jiawei Zhang
Graph classification is a critical research problem in many applications from different domains. In order to learn a graph classification model, the most widely used supervision co…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
Deoscillated Graph Collaborative Filtering
Zhiwei Liu, Lin Meng, Fei Jiang +2
Collaborative Filtering (CF) signals are crucial for a Recommender System~(RS) model to learn user and item embeddings. High-order information can alleviate the cold-start issue of…
Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning
Yizhu Jiao, Yun Xiong, Jiawei Zhang +3
Graph representation learning has attracted lots of attention recently. Existing graph neural networks fed with the complete graph data are not scalable due to limited computation…
G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning
Jiawei Zhang
The recent GRAPH-BERT model introduces a new approach to learning graph representations merely based on the attention mechanism. GRAPH-BERT provides an opportunity for transferring…
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo +1
Non-local self-similarity in natural images has been well studied as an effective prior in image restoration. However, for single image super-resolution (SISR), most existing deep…
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection
Congying Xia, Chenwei Zhang, Hoang Nguyen +2
In this paper, we formulate a more realistic and difficult problem setup for the intent detection task in natural language understanding, namely Generalized Few-Shot Intent Detecti…
Graph Neural Distance Metric Learning with Graph-Bert
Jiawei Zhang
Graph distance metric learning serves as the foundation for many graph learning problems, e.g., graph clustering, graph classification and graph matching. Existing research works o…
Segmented Graph-Bert for Graph Instance Modeling
Jiawei Zhang
In graph instance representation learning, both the diverse graph instance sizes and the graph node orderless property have been the major obstacles that render existing representa…
Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
Graph neural networks (GNNs) have achieved outstanding performance in learning graph-structured data and various tasks. However, many current GNNs suffer from three common problems…