Publications (133)
Contrastive Learning Meets Pseudo-label-assisted Mixup Augmentation: A Comprehensive Graph Representation Framework from Local to Global
Jinlu Wang, Yanfeng Sun, Jiapu Wang +3
Unleash Graph Neural Networks from Heavy Tuning
Lequan Lin, Dai Shi, Andi Han +2
SVDformer: Direction-Aware Spectral Graph Embedding Learning via SVD and Transformer
Jiayu Fang, Zhiqi Shao, S T Boris Choy +1
MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning
Xuebin Zheng, Bingxin Zhou, Ming Li +2
Locality Preserving Projections for Grassmann manifold
Boyue Wang, Yongli Hu, Junbin Gao +3
Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with Heterophily
Jie Chen, Shouzhen Chen, Junbin Gao +3
SGNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning
Dai Shi, Luke Thompson, Linhan Luo +4
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP
Jie Chen, Shouzhen Chen, Mingyuan Bai +3
Machine Learning-Based Prediction of Key Genes Correlated to the Subretinal Lesion Severity in a Mouse Model of Age-Related Macular Degeneration
Kuan Yan, Yue Zeng, Dai Shi +5
Partial Sum Minimization of Singular Values Representation on Grassmann Manifolds
Boyue Wang, Yongli Hu, Junbin Gao +2
Riemannian Hamiltonian methods for min-max optimization on manifolds
Andi Han, Bamdev Mishra, Pratik Jawanpuria +2
Tractable Clustering of Data on the Curve Manifold
Stephen Tierney, Junbin Gao, Yi Guo +1
Kernelized Low Rank Representation on Grassmann Manifolds
Boyue Wang, Yongli Hu, Junbin Gao +2
A Simple Yet Effective SVD-GCN for Directed Graphs
Chunya Zou, Andi Han, Lequan Lin +1
How Framelets Enhance Graph Neural Networks
Xuebin Zheng, Bingxin Zhou, Junbin Gao +4
Riemannian stochastic recursive momentum method for non-convex optimization
Andi Han, Junbin Gao
Graph Denoising with Framelet Regularizer
Bingxin Zhou, Ruikun Li, Xuebin Zheng +2
Mixture of Bilateral-Projection Two-dimensional Probabilistic Principal Component Analysis
Fujiao Ju, Yanfeng Sun, Junbin Gao +2
Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond
Dai Shi, Kuan Yan, Lequan Lin +6
Riemannian block SPD coupling manifold and its application to optimal transport
Andi Han, Bamdev Mishra, Pratik Jawanpuria +1
A Heuristic Algorithm Based on Tour Rebuilding Operator for the Traveling Salesman Problem
Yang Li, Junbin Gao, Mingyuan Bai +2
Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
Dai Shi, Lequan Lin, Andi Han +4
Signals, Concepts, and Laws: Toward Universal, Explainable Time-Series Forecasting
Hongwei Ma, Junbin Gao, Minh-Ngoc Tran
Hierarchical Multi-modal Transformer for Cross-modal Long Document Classification
Tengfei Liu, Yongli Hu, Junbin Gao +2
Wasserstein Adversarially Regularized Graph Autoencoder
Huidong Liang, Junbin Gao
Segmentation of Subspaces in Sequential Data
Stephen Tierney, Yi Guo, Junbin Gao
Tensorial Recurrent Neural Networks for Longitudinal Data Analysis
Mingyuan Bai, Boyan Zhang, Junbin Gao
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion
Dai Shi, Zhiqi Shao, Yi Guo +2
A Review for Weighted MinHash Algorithms
Wei Wu, Bin Li, Ling Chen +2
Neighborhood Preserved Sparse Representation for Robust Classification on Symmetric Positive Definite Matrices
Ming Yin, Shengli Xie, Yi Guo +2
A Discussion On the Validity of Manifold Learning
Dai Shi, Andi Han, Yi Guo +1
Kernelized LRR on Grassmann Manifolds for Subspace Clustering
Boyue Wang, Yongli Hu, Junbin Gao +2
ACT as Human: Multimodal Large Language Model Data Annotation with Critical Thinking
Lequan Lin, Dai Shi, Andi Han +7
ST-MambaSync: The Complement of Mamba and Transformers for Spatial-Temporal in Traffic Flow Prediction
Zhiqi Shao, Xusheng Yao, Ze Wang +1
Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradient
Andi Han, Junbin Gao
Riemannian accelerated gradient methods via extrapolation
Andi Han, Bamdev Mishra, Pratik Jawanpuria +1
Learning Manifold and Itô Dynamics with Branched Neural Rough Differential Equations
Luke Thompson, Dai Shi, Lequan Lin +2
Quasi-Framelets: Robust Graph Neural Networks via Adaptive Framelet Convolution
Mengxi Yang, Dai Shi, Xuebin Zheng +2
CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model
Zhiqi Shao, Michael G. H. Bell, Ze Wang +3
DataLearner: A Data Mining and Knowledge Discovery Tool for Android Smartphones and Tablets
Darren Yates, Md Zahidul Islam, Junbin Gao
From Noise to Laws: Regularized Time-Series Forecasting via Denoised Dynamic Graphs
Hongwei Ma, Junbin Gao, Minh-ngoc Tran
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond
Zhiqi Shao, Dai Shi, Andi Han +3
Matrix Variate RBM Model with Gaussian Distributions
Simeng Liu, Yanfeng Sun, Yongli Hu +2
ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
Luke Thompson, Davy Guan, Dai Shi +3
Contrastive Identification and Generation in the Limit
Xiaoyu Li, Andi Han, Jiaojiao Jiang +1
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations
Jinlu Wang, Jipeng Guo, Yanfeng Sun +4
Low Rank Representation on Grassmann Manifolds: An Extrinsic Perspective
Boyue Wang, Yongli Hu, Junbin Gao +2
Low-rank Multi-view Clustering in Third-Order Tensor Space
Ming Yin, Junbin Gao, Shengli Xie +1
Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit
Xiaoyu Li, Andi Han, Dai Shi +3
Matrix Variate RBM and Its Applications
Guanglei Qi, Yanfeng Sun, Junbin Gao +2
Graph Signal Processing for Global Stock Market Realized Volatility Forecasting
Zhengyang Chi, Junbin Gao, Chao Wang
Sparse Least Squares Low Rank Kernel Machines
Di Xu, Manjing Fang, Xia Hong +1
A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphs
Lequan Lin, Junbin Gao
Fast Optimization Algorithm on Riemannian Manifolds and Its Application in Low-Rank Representation
Haoran Chen, Yanfeng Sun, Junbin Gao +1
Coupling Matrix Manifolds and Their Applications in Optimal Transport
Dai Shi, Junbin Gao, Xia Hong +2
Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment
Qijie Ding, Jie Yin, Daokun Zhang +1
LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
Lanxin Zhao, Bamdev Mishra, Pratik Jawanpuria +4
Assessing the Performance of Deep Learning Algorithms for Newsvendor Problem
Yanfei Zhang, Junbin Gao
Variance reduction for Riemannian non-convex optimization with batch size adaptation
Andi Han, Junbin Gao
Tensor Sparse and Low-Rank based Submodule Clustering Method for Multi-way Data
Xinglin Piao, Yongli Hu, Junbin Gao +3
Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
Yachao Yang, Yanfeng Sun, Jipeng Guo +4
Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks
Dai Shi, Andi Han, Lequan Lin +3
Collaborative Low-Rank Subspace Clustering
Stephen Tierney, Yi Guo, Junbin Gao
Scalable Nuclear-norm Minimization by Subspace Pursuit Proximal Riemannian Gradient
Mingkui Tan, Shijie Xiao, Junbin Gao +3
ST-Mamba: Spatial-Temporal Selective State Space Model for Traffic Flow Prediction
Zhiqi Shao, Michael G. H. Bell, Ze Wang +3
Robust Graph Representation Learning for Local Corruption Recovery
Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang +4
Tensor-Train Parameterization for Ultra Dimensionality Reduction
Mingyuan Bai, S. T. Boris Choy, Xin Song +1
A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting
Zhengkun Li, Minh-Ngoc Tran, Chao Wang +2
Bregman Graph Neural Network
Jiayu Zhai, Lequan Lin, Dai Shi +1
Regularized Flexible Activation Function Combinations for Deep Neural Networks
Renlong Jie, Junbin Gao, Andrey Vasnev +1
Generalized Laplacian Regularized Framelet Graph Neural Networks
Zhiqi Shao, Andi Han, Dai Shi +2
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
Andi Han, Bamdev Mishra, Pratik Jawanpuria +1
Beyond Averaging in John Ellipsoid Approximation: High-Accuracy Algorithms in the Leverage-Score Model
Xiaoyu Li, Junwei Yu, Jiaojiao Jiang +2
Graph Contrastive Learning with Implicit Augmentations
Huidong Liang, Xingjian Du, Bilei Zhu +3
Frameless Graph Knowledge Distillation
Dai Shi, Zhiqi Shao, Yi Guo +1
Universal Deep GNNs: Rethinking Residual Connection in GNNs from a Path Decomposition Perspective for Preventing the Over-smoothing
Jie Chen, Weiqi Liu, Zhizhong Huang +3
Engineering Carbon Credits Towards A Responsible FinTech Era: The Practices, Implications, and Future
Qingwen Zeng, Hanlin Xu, Nanjun Xu +5
Adaptive Hierarchical Hyper-gradient Descent
Renlong Jie, Junbin Gao, Andrey Vasnev +1
On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods
Bingxin Zhou, Xuebin Zheng, Junbin Gao
PREIG: Physics-informed and Reinforcement-driven Interpretable GRU for Commodity Demand Forecasting
Hongwei Ma, Junbin Gao, Minh-Ngoc Tran
Manifold Optimization Assisted Gaussian Variational Approximation
Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran +1
Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification
Lin Wu, Yang Wang, Junbin Gao +1
On the Price of Privacy for Language Identification and Generation
Xiaoyu Li, Andi Han, Jiaojiao Jiang +1
When Graph Neural Networks Meet Dynamic Mode Decomposition
Dai Shi, Lequan Lin, Andi Han +3
Efficient Sparse Subspace Clustering by Nearest Neighbour Filtering
Stephen Tierney, Yi Guo, Junbin Gao
OTExtSum: Extractive Text Summarisation with Optimal Transport
Peggy Tang, Kun Hu, Rui Yan +3
SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operators
Pengqing Shi, Jie Yin, Stephen Tierney +1
Diffusion Models for Time Series Applications: A Survey
Lequan Lin, Zhengkun Li, Ruikun Li +2
Embedding Graphs on Grassmann Manifold
Bingxin Zhou, Xuebin Zheng, Yu Guang Wang +2
How Curvature Enhance the Adaptation Power of Framelet GCNs
Dai Shi, Yi Guo, Zhiqi Shao +1
Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering
Tianxiang Zhao, Youqing Wang, Jinlu Wang +4
Variational Counterfactual Prediction under Runtime Domain Corruption
Hechuan Wen, Tong Chen, Li Kheng Chai +3
STPFormer: A State-of-the-Art Pattern-Aware Spatio-Temporal Transformer for Traffic Forecasting
Jiayu Fang, Zhiqi Shao, S T Boris Choy +1
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond
Andi Han, Dai Shi, Lequan Lin +1
Partial Least Squares Regression on Riemannian Manifolds and Its Application in Classifications
Haoran Chen, Yanfeng Sun, Junbin Gao +2
Relations among Some Low Rank Subspace Recovery Models
Hongyang Zhang, Zhouchen Lin, Chao Zhang +1
A Riemannian Approach to Ground Metric Learning for Optimal Transport
Pratik Jawanpuria, Dai Shi, Bamdev Mishra +1
Matrix Neural Networks
Junbin Gao, Yi Guo, Zhiyong Wang
Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification
Lin Wu, Yang Wang, Junbin Gao +1
Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multi-Camera Video Surveillance
Boyue Wang, Yongli Hu, Junbin Gao +2