Yatao Bian

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 89

Top Topics

Graph Representation

Variational Inference

Top Venues

Publications

Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian
HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. CoRR (2024)
Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
How Interpretable Are Interpretable Graph Neural Networks? CoRR (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD (2024)
Ziqiao Zhang, Yatao Bian, Ailin Xie, Pengju Han, Shuigeng Zhou
Can Pretrained Models Really Learn Better Molecular Representations for AI-Aided Drug Discovery? J. Chem. Inf. Model. 64 (7) (2024)
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Recognizing Predictive Substructures With Subgraph Information Bottleneck. IEEE Trans. Pattern Anal. Mach. Intell. 46 (3) (2024)
Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. CoRR (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR (2024)
Huaijin Wu, Wei Liu, Yatao Bian, Jiaxiang Wu, Nianzu Yang, Junchi Yan
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model. ICLR (2024)
Haiquan Qiu, Yatao Bian, Quanming Yao
Graph Unitary Message Passing. CoRR (2024)
Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong
WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR (2024)
Youzhi Qu, Chen Wei, Penghui Du, Wenxin Che, Chi Zhang, Wanli Ouyang, Yatao Bian, Feiyang Xu, Bin Hu, Kai Du, Haiyan Wu, Jia Liu, Quanying Liu
Integration of cognitive tasks into artificial general intelligence test for large models. CoRR (2024)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM (2024)
Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu
Fairness-guided Few-shot Prompting for Large Language Models. CoRR (2023)
Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang, Jingsong Lv, Hongyang Chen, Huajun Chen
Learning Invariant Molecular Representation in Latent Discrete Space. NeurIPS (2023)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR (2023)
Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR (2023)
Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
Simplifying and Empowering Transformers for Large-Graph Representations. CoRR (2023)
Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. EMNLP (2023)
Ziqiao Zhang, Bangyi Zhao, Ailin Xie, Yatao Bian, Shuigeng Zhou
Activity Cliff Prediction: Dataset and Benchmark. CoRR (2023)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS (2023)
Haotian Wang, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, Bingzhe Wu
RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data. EMNLP (Findings) (2023)
Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang, Jingsong Lv, Hongyang Chen, Huajun Chen
Learning Invariant Molecular Representation in Latent Discrete Space. CoRR (2023)
Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. CoRR (2023)
Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR (2023)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS (2023)
Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. ICLR (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM (2023)
Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu
Curriculum Graph Poisoning. WWW (2023)
Yiqiang Yi, Xu Wan, Yatao Bian, Le Ou-Yang, Peilin Zhao
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking. CoRR (2023)
Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
Simplifying and Empowering Transformers for Large-Graph Representations. NeurIPS (2023)
Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu
Fairness-guided Few-shot Prompting for Large Language Models. NeurIPS (2023)
Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR (2023)
Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao
Reweighted Mixup for Subpopulation Shift. CoRR (2023)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR (2023)
Yuanfeng Ji, Yatao Bian, Guoji Fu, Peilin Zhao, Ping Luo
SyNDock: N Rigid Protein Docking via Learnable Group Synchronization. CoRR (2023)
Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li, Junzhou Huang
MoDNA: motif-oriented pre-training for DNA language model. BCB (2022)
Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. CoRR (2022)
Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport. CoRR (2022)
Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang, Yinglu Zhang, Jihong Guan, Yatao Bian, Shuigeng Zhou
Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method. ACM Multimedia (2022)
Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport. IJCAI (2022)
Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong
Transformer for Graphs: An Overview from Architecture Perspective. CoRR (2022)
Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer. SIGIR (2022)
Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang, Yinglu Zhang, Jihong Guan, Yatao Bian, Shuigeng Zhou
Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method. CoRR (2022)
Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR (2022)
Guoji Fu, Peilin Zhao, Yatao Bian
p-Laplacian Based Graph Neural Networks. ICML (2022)
Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. ICLR (2022)
Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Junzhou Huang, Da Luo, Kangyi Lin, Sophia Ananiadou
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction. CoRR (2022)
Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR (2022)
Ziqiao Zhang, Yatao Bian, Ailin Xie, Pengju Han, Long-Kai Huang, Shuigeng Zhou
Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery? CoRR (2022)
Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian
Learning Neural Set Functions Under the Optimal Subset Oracle. NeurIPS (2022)
Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD (2022)
Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR (2022)
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR (2022)
Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS (2022)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
Pareto Invariant Risk Minimization. CoRR (2022)
Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS (2022)
Erxue Min, Yu Rong, Yatao Bian, Tingyang Xu, Peilin Zhao, Junzhou Huang, Sophia Ananiadou
Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media. WWW (2022)
Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang
Cross-dependent graph neural networks for molecular property prediction. Bioinform. 38 (7) (2022)
Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian
Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. CoRR (2022)
Xi Leng, Xiaoying Tang, Yatao Bian
Diversity Boosted Learning for Domain Generalization with Large Number of Domains. CoRR (2022)
Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR (2022)
Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian
Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs. CoRR (2022)
Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong
Diversified Multiscale Graph Learning with Graph Self-Correction. TAG-ML (2022)
Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR (2022)
Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang
On Self-Distilling Graph Neural Network. IJCAI (2021)
Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang
Diversified Multiscale Graph Learning with Graph Self-Correction. CoRR (2021)
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Recognizing Predictive Substructures with Subgraph Information Bottleneck. CoRR (2021)
Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu
Not All Low-Pass Filters are Robust in Graph Convolutional Networks. NeurIPS (2021)
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi Jaakkola, Andreas Krause
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. CoRR (2021)
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Graph Information Bottleneck for Subgraph Recognition. ICLR (2021)
Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations. CoRR (2021)
Bingzhe Wu, Zhicong Liang, Yatao Bian, Chaochao Chen, Junzhou Huang, Yuan Yao
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis. CoRR (2021)
Guoji Fu, Peilin Zhao, Yatao Bian
p-Laplacian Based Graph Neural Networks. CoRR (2021)
Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang
Dual Message Passing Neural Network for Molecular Property Prediction. CoRR (2020)
Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. CoRR (2020)
Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
Self-Supervised Graph Transformer on Large-Scale Molecular Data. NeurIPS (2020)
Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML (2020)
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Graph Information Bottleneck for Subgraph Recognition. CoRR (2020)
Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang
On Self-Distilling Graph Neural Network. CoRR (2020)
Yatao Bian, Joachim M. Buhmann, Andreas Krause
Continuous Submodular Function Maximization. CoRR (2020)
Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data. CoRR (2020)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Greedy MAXCUT Algorithms and their Information Content. CoRR (2016)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Information-theoretic analysis of MaxCut algorithms. ITA (2016)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Greedy MaxCut algorithms and their information content. ITW (2015)
Yatao Bian, Xiong Li, Mingqi Cao, Yuncai Liu
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression. ECML/PKDD (3) (2013)
Yatao Bian, Xiong Li, Yuncai Liu
Parallel Coordinate Descent Newton for Large-scale L1-Regularized Minimization. CoRR (2013)
Jian Song, Yatao Bian, Junchi Yan, Xu Zhao, Yuncai Liu
Digitize Your Body and Action in 3-D at Over 10 FPS: Real Time Dense Voxel Reconstruction and Marker-less Motion Tracking via GPU Acceleration. CoRR (2013)
Yatao Bian, Xu Zhao, Jian Song, Yuncai Liu
Parallelized Annealed Particle Filter for real-time marker-less motion tracking via heterogeneous computing. ICPR (2012)