Tingyang Xu

发表

Self-Supervised Graph Transformer on Large-Scale Molecular Data

Yatao Bian, Junzhou Huang, Wen-bing Huang, 2020, NeurIPS.

Not All Low-Pass Filters are Robust in Graph Convolutional Networks

Yatao Bian, Junzhou Huang, Wenwu Zhu, 2021, NeurIPS.

Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media

Yatao Bian, Junzhou Huang, P. Zhao, 2022, WWW.

DROPEDGE: TOWARDS DEEP GRAPH CONVOLU-

Junzhou Huang, Yu Rong, Tingyang Xu, 2019 .

Molecular Graph Enhanced Transformer for Retrosynthesis Prediction

Junzhou Huang, P. Zhao, Xi Xiao, 2019, bioRxiv.

Genome-wide Association Analysis

J. Bi, Tingyang Xu, Jiangwen Sun, 2015 .

Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents

Qifeng Bai, Tingyang Xu, Lanqing Li, 2022, Computational and structural biotechnology journal.

Spatio-Temporal Modeling of EEG Data for Understanding Working Memory

J. Bi, Chi-Ming A. Chen, Tingyang Xu, 2015 .

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning

Yatao Bian, Jiaxiang Wu, Junzhou Huang, 2021, ICLR.

Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction

Xinchao Wang, Jiashi Feng, Tingyang Xu, 2022, ArXiv.

Junzhou Huang, Wen-bing Huang, Yu Rong, 2022, ArXiv.

Blood–brain barrier penetration prediction enhanced by uncertainty estimation

Junzhou Huang, Qun Ren, Xutong Li, 2022, Journal of Cheminformatics.

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection

Yatao Bian, Zibin Zheng, Junzhou Huang, 2022, ArXiv.

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations pdf

Junzhou Huang, Yu Rong, Tingyang Xu, 2021, ArXiv.

Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs

Yatao Bian, Junzhou Huang, Yu Rong, 2022, ArXiv.

Learning Neural Set Functions Under the Optimal Subset Oracle

Yatao Bian, Yingzhen Li, P. Zhao, 2022, 2203.01693.

Local Augmentation for Graph Neural Networks

Junzhou Huang, P. Zhao, Dinghao Wu, 2021, ICML.

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Junzhou Huang, Yu Rong, Tingyang Xu, 2019, ICLR.

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Junzhou Huang, Yu Rong, Tingyang Xu, 2019, International Conference on Learning Representations.

Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

Yatao Bian, Junzhou Huang, P. Zhao, 2022, SIGIR.

Toward Complete-View and High-Level Pose-Based Gait Recognition

Yongyong Chen, Tingyang Xu, Honghu Pan, 2022, IEEE Transactions on Information Forensics and Security.

Junzhou Huang, Wen-bing Huang, Yu Rong, 2022, ArXiv.

Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax

F. Tsung, Nuo Chen, Yu Rong, 2022, AAAI.

Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks pdf

Wenbing Huang, Junzhou Huang, Xi Xiao, 2020, AAAI.

Graph Representation Learning via Graphical Mutual Information Maximization

Minnan Luo, Zhen Peng, Tingyang Xu, 2020, WWW.

Drug repurposing against breast cancer by integrating drug-exposure expression profiles and drug–drug links based on graph neural network

Xiaomin Luo, Kaixian Chen, Hualiang Jiang, 2021, Bioinform..

Deep Multimodal Fusion by Channel Exchanging pdf

Fuchun Sun, Yikai Wang, Tingyang Xu, 2020, NeurIPS.

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm

Tingyang Xu, Junzhou Huang, Huanxiang Liu, 2020, Briefings Bioinform..

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization

Jinbo Bi, Jin Lu, Jiangwen Sun, 2015, ICML.

WADDAICA: A webserver for aiding protein drug design by artificial intelligence and classical algorithm

Junzhou Huang, Qifeng Bai, Huanxiang Liu, 2021, Computational and structural biotechnology journal.

Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding

Junzhou Huang, Yue Huang, Yu Rong, 2021, CIKM.

Unsupervised Adversarial Graph Alignment with Graph Embedding pdf

Wenbing Huang, Yue Huang, Xinghao Ding, 2019, ArXiv.

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations

Junzhou Huang, Yu Rong, Shuigeng Zhou, 2022, ArXiv.

Development and Validation of an Image-based Deep Learning Algorithm for Detection of Synchronous Peritoneal Carcinomatosis in Colorectal Cancer

Jianhua Yao, A. Fichera, Tingyang Xu, 2020, Annals of surgery.

Geometrically Equivariant Graph Neural Networks: A Survey

Yu Rong, Tingyang Xu, Wenbing Huang, 2022, ArXiv.

Translating Effective Paper-Based Disease Management into Electronic Medical Systems

Jinbo Bi, Tingyang Xu, Michelle M. Cloutier, 2014, 2014 IEEE International Conference on Healthcare Informatics.

Generative Models for De Novo Drug Design.

Hualiang Jiang, Xutong Li, Zhaoping Xiong, 2021, Journal of medicinal chemistry.

MDM: Molecular Diffusion Model for 3D Molecule Generation

Ka-chun Wong, Tingyang Xu, Hengtong Zhang, 2022, AAAI.

Equivariant Graph Mechanics Networks with Constraints

Junzhou Huang, Wen-bing Huang, Yu Rong, 2022, ICLR.

Multi-View Graph Neural Networks for Molecular Property Prediction

Wenbing Huang, Junzhou Huang, Yu Rong, 2020, 2005.13607.

A dual diffusion model enables 3D binding bioactive molecule generation and lead optimization given target pockets

P. Zhao, Ka-chun Wong, Tingyang Xu, 2023, bioRxiv.

Progressive Feature Alignment for Unsupervised Domain Adaptation

Junzhou Huang, Xinghao Ding, Tingyang Xu, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Towards the Explanation of Graph Neural Networks in Digital Pathology with Information Flows pdf

Tingyang Xu, Junchi Yu, Ran He, 2021, ArXiv.

Graph Information Bottleneck for Subgraph Recognition pdf

Yu Rong, Tingyang Xu, Ran He, 2020, ICLR.

The Truly Deep Graph Convolutional Networks for Node Classification pdf

Wenbing Huang, Tingyang Xu, Junzhou Huang, 2019, ArXiv.

Multi-instance learning of graph neural networks for aqueous pKa prediction

Feisheng Zhong, Tingyang Xu, Zhaojun Li, 2021, Bioinform..

Rethinking and Relieving Over-Smoothing in Deep GCNs

Fuchun Sun, Yu Rong, Tingyang Xu, 2020 .

Equivariant Graph Hierarchy-Based Neural Networks

Yu Rong, Tingyang Xu, Wenbing Huang, 2022, NeurIPS.

On Self-Distilling Graph Neural Network

Yatao Bian, Junzhou Huang, Xi Xiao, 2020, IJCAI.

Spectral Graph Attention Network with Fast Eigen-approximation

Junzhou Huang, Wenwu Zhu, Yu Rong, 2020, CIKM.

Adversarial Attack Framework on Graph Embedding Models With Limited Knowledge

Junzhou Huang, Wenwu Zhu, Xin Wang, 2021, IEEE Transactions on Knowledge and Data Engineering.

DTWNet: a Dynamic Time Warping Network

Sanguthevar Rajasekaran, Jinfeng Yi, Junzhou Huang, 2019, NeurIPS.

Tackling Over-Smoothing for General Graph Convolutional Networks

Junzhou Huang, Yu Rong, Tingyang Xu, 2020, ArXiv.

Application advances of deep learning methods for de novo drug design and molecular dynamics simulation

Junzhou Huang, Huanxiang Liu, Qifeng Bai, 2021, WIREs Computational Molecular Science.

Recognizing Predictive Substructures With Subgraph Information Bottleneck

Junzhou Huang, Ran He, Yu Rong, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference

Yatao Bian, Yingzhen Li, P. Zhao, 2022, ArXiv.

Transformer for Graphs: An Overview from Architecture Perspective

Yatao Bian, Junzhou Huang, P. Zhao, 2022, ArXiv.

Structure-aware conditional variational auto-encoder for constrained molecule optimization

Junzhou Huang, Yu Rong, Tingyang Xu, 2022, Pattern Recognit..

An Effective Tensor Regression with Latent Sparse Regularization

J. Bi, Minghu Song, Tingyang Xu, 2022, Journal of Data Science.

Curriculum Graph Poisoning

Yatao Bian, Junzhou Huang, Yadong Mu, 2023, WWW.

A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models

Wenbing Huang, Junzhou Huang, Honglei Zhang, 2019, AAAI.

Learning Neural Set Functions Under the Optimal Subset Oracle

Yatao Bian, Yingzhen Li, P. Zhao, 2022, NeurIPS.

A Novel Scalarized Scaffold Hopping Algorithm with Graph-Based Variational Autoencoder for Discovery of JAK1 Inhibitors

Junzhou Huang, Yu Rong, Tingyang Xu, 2021, ACS omega.

Identifying and quantifying nonlinear structured relationships in complex manufactural systems

Wei Cheng, Jinbo Bi, Haifeng Chen, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

Yixuan Li, Junzhou Huang, Tongliang Liu, 2021, 2106.07451.

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks

Junzhou Huang, Wen-bing Huang, Yu Rong, 2023, ArXiv.

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

P. Zhao, F. Tsung, Tingyang Xu, 2022, AAAI.

Towards Controllable Diffusion Models via Reward-Guided Exploration

Tingyang Xu, Heng Zhang, 2023, ArXiv.

Molecular Graph Enhanced Transformer for Retrosynthesis Prediction

Junzhou Huang, Yu Rong, Kelong Mao, 2019, bioRxiv.

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Jinbo Bi, Jiangwen Sun, Tingyang Xu, 2015, KDD.

Adversarial Attack Framework on Graph Embedding Models With Limited Knowledge pdf

Junzhou Huang, Wenwu Zhu, Peng Cui, 2021, IEEE Transactions on Knowledge and Data Engineering.

Deep Graph Learning: Foundations, Advances and Applications

Wenbing Huang, Hong Cheng, Tingyang Xu, 2020, KDD.

Dual Message Passing Neural Network for Molecular Property Prediction pdf

Junzhou Huang, Yu Rong, Tingyang Xu, 2020, ArXiv.

Spectral Graph Attention Network pdf

Somayeh Sojoudi, Heng Chang, Tingyang Xu, 2020, ArXiv.

GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data pdf

Wenbing Huang, Junzhou Huang, Yu Rong, 2020, ArXiv.

Diversified Multiscale Graph Learning with Graph Self-Correction pdf

Junzhou Huang, Xi Xiao, Yu Rong, 2021, TAG-ML.

Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation

Junzhou Huang, Sheng Wang, Tingyang Xu, 2019, BCB.

Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?

Junzhou Huang, P. Zhao, Xi Xiao, 2020, ArXiv.

A Bisection Reinforcement Learning Approach to 3-D Indoor Localization

Jinbo Bi, Jin Lu, Tingyang Xu, 2021, IEEE Internet of Things Journal.

Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design.

L. Yao, Tingyang Xu, Wei Huang, 2023, ACS medicinal chemistry letters.

Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction

Yatao Bian, Junzhou Huang, P. Zhao, 2022, ArXiv.

GPN: A Joint Structural Learning Framework for Graph Neural Networks

P. Zhao, Deheng Ye, Tingyang Xu, 2022, ArXiv.

Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation

Yu Rong, Tingyang Xu, Wenbing Huang, 2022, ArXiv.

Computing Graph Edit Distance via Neural Graph Matching

Yu Rong, Tingyang Xu, Xiangguo Sun, 2023, Proceedings of the VLDB Endowment.

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations

Yatao Bian, Jiaxiang Wu, Junzhou Huang, 2023, AAAI.

Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction

P. Zhao, Xinchao Wang, Bryan Hooi, 2022, LoG.

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels pdf

Junzhou Huang, Yu Rong, Tingyang Xu, 2021, ArXiv.

Latent Sparse Modeling of Longitudinal Multi-Dimensional Data

Jinbo Bi, Tingyang Xu, Ko-Shin Chen, 2018, AAAI.

Jointly Learning Features and Temporal Contingency for Prediction in Large Scale Datasets

Tingyang Xu, Tingyang Xu, 2017 .

A sparse integrative cluster analysis for understanding soybean phenotypes

Jinbo Bi, Yansong Ma, Jin Lu, 2014, 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

Yatao Bian, Junzhou Huang, P. Zhao, 2022, SIGIR.

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation

P. Zhao, F. Tsung, Tingyang Xu, 2023, ArXiv.

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning

Junzhou Huang, Yu Rong, Andreas Krause, 2021, International Conference on Learning Representations.

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

Tingyang Xu, Hongteng Xu, Rui Jiao, 2024, ArXiv.

A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models

Junzhou Huang, Wenwu Zhu, Peng Cui, 2019, AAAI.

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning

Yatao Bian, Jiaxiang Wu, Junzhou Huang, 2021, ICLR.

Geometric deep learning methods and applications in 3D structure-based drug design.

Tingyang Xu, Horacio Pérez-Sánchez, Junzhou Huang, 2024, Drug discovery today.

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping

Tingyang Xu, Guozheng Ma, Ziqiao Meng, 2024, ArXiv.