Yatao Bian - RankMe

119 papers A* 38A 2B 2Misc 1Journal 69Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Versatile Image Generation. CoRR Jinmei Liu, Haoru Li, Zhenhong Sun, Chaofeng Chen, Yatao Bian, Bo Wang, Daoyi Dong, Chunlin Chen, Zhi Wang
2026	A*	`conf`	CrystalDiT: Simple Diffusion Transformers for Crystal Generation. AAAI Xiaohan Yi, Guikun Xu, Zhong Zhang, Liu Liu, Yatao Bian, Xi Xiao, Peilin Zhao
2026	J	`jnl`	Learning hierarchical time-frequency representation for long-term time series forecasting. Inf. Process. Manag. Zhongju Wang, Zhenhong Sun, Yatao Bian, Huadong Mo, Daoyi Dong
2025	J	`jnl`	3D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding. CoRR Chang Wu, Zhiyuan Liu, Wen Shu, Liang Wang, Yanchen Luo, Wenqiang Lei, Yatao Bian, Junfeng Fang, Xiang Wang
2025	J	`jnl`	A Unified Random Walk, Its Induced Laplacians and Spectral Convolutions for Deep Hypergraph Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jiying Zhang, Fuyang Li, Xi Xiao, Guanzi Chen, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian
2025	A*	`conf`	COME: Test-time Adaption by Conservatively Minimizing Entropy. ICLR Qingyang Zhang, Yatao Bian, Xinke Kong, Peilin Zhao, Changqing Zhang
2025	J	`jnl`	CrystalDiT: A Diffusion Transformer for Crystal Generation. CoRR Xiaohan Yi, Guikun Xu, Xi Xiao, Zhong Zhang, Liu Liu, Yatao Bian, Peilin Zhao
2025	J	`jnl`	Energy-Guided Flow Matching Enables Few-Step Conformer Generation and Ground-State Identification. CoRR Guikun Xu, Xiaohan Yi, Peilin Zhao, Yatao Bian
2025	A*	`conf`	Erasing Concept Combination from Text-to-Image Diffusion Model. ICLR Hongyi Nie, Quanming Yao, Yang Liu, Zhen Wang, Yatao Bian
2025	A*	`conf`	Hierarchical Graph Tokenization for Molecule-Language Alignment. ICML Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian
2025	A*	`conf`	InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization. ICLR Yifan Niu, Ziqi Gao, Tingyang Xu, Yang Liu, Yatao Bian, Yu Rong, Junzhou Huang, Jia Li
2025	J	`jnl`	InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization. CoRR Yifan Niu, Ziqi Gao, Tingyang Xu, Yang Liu, Yatao Bian, Yu Rong, Junzhou Huang, Jia Li
2025	A*	`conf`	Measuring Diversity in Synthetic Datasets. ICML Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng, Peilin Zhao, Liang Chen, Yatao Bian
2025	J	`jnl`	Measuring Diversity in Synthetic Datasets. CoRR Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng, Peilin Zhao, Liang Chen, Yatao Bian
2025	—	`conf`	RelEdit: Evaluating Conceptual Knowledge Editing in Language Models via Relational Reasoning. ACL (Findings) Yifan Niu, Miao Peng, Nuo Chen, Yatao Bian, Tingyang Xu, Jia Li
2025	J	`jnl`	Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization. CoRR Qingyang Zhang, Haitao Wu, Changqing Zhang, Peilin Zhao, Yatao Bian
2025	J	`jnl`	Think Consistently, Reason Efficiently: Energy-Based Calibration for Implicit Chain-of-Thought. CoRR Zhikang Chen, Sen Cui, Deheng Ye, Yu Zhang, Yatao Bian, Tingting Zhu
2025	A*	`conf`	Unified Molecule-Text Language Model with Discrete Token Representation. IJCAI Shuhan Guo, Yatao Bian, Ruibing Wang, Nan Yin, Zhen Wang, Quanming Yao
2024	J	`jnl`	COME: Test-time adaption by Conservatively Minimizing Entropy. CoRR Qingyang Zhang, Yatao Bian, Xinke Kong, Peilin Zhao, Changqing Zhang
2024	J	`jnl`	Can Pretrained Models Really Learn Better Molecular Representations for AI-Aided Drug Discovery? J. Chem. Inf. Model. Ziqiao Zhang, Yatao Bian, Ailin Xie, Pengju Han, Shuigeng Zhou
2024	J	`jnl`	ConML: A Universal Meta-Learning Framework with Task-Level Contrastive Learning. CoRR Shiguang Wu, Yaqing Wang, Yatao Bian, Quanming Yao
2024	A*	`conf`	EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model. ICLR Huaijin Wu, Wei Liu, Yatao Bian, Jiaxiang Wu, Nianzu Yang, Junchi Yan
2024	A*	`conf`	Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
2024	J	`jnl`	Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
2024	J	`jnl`	Graph Unitary Message Passing. CoRR Haiquan Qiu, Yatao Bian, Quanming Yao
2024	J	`jnl`	HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment. CoRR Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian
2024	A*	`conf`	How Interpretable Are Interpretable Graph Neural Networks? ICML Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
2024	J	`jnl`	How Interpretable Are Interpretable Graph Neural Networks? CoRR Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
2024	J	`jnl`	Integration of cognitive tasks into artificial general intelligence test for large models. CoRR 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
2024	A*	`conf`	One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
2024	J	`jnl`	One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
2024	J	`jnl`	Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation. CoRR Haoyu Wang, Bingzhe Wu, Yatao Bian, Yongzhe Chang, Xueqian Wang, Peilin Zhao
2024	J	`jnl`	Recognizing Predictive Substructures With Subgraph Information Bottleneck. IEEE Trans. Pattern Anal. Mach. Intell. Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
2024	A	`conf`	Rethinking and Simplifying Bootstrapped Graph Latents. WSDM Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
2024	J	`jnl`	Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. CoRR Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao
2024	A*	`conf`	The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection. NeurIPS Qingyang Zhang, Qiuxuan Feng, Joey Tianyi Zhou, Yatao Bian, Qinghua Hu, Changqing Zhang
2024	J	`jnl`	The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection. CoRR Qingyang Zhang, Qiuxuan Feng, Joey Tianyi Zhou, Yatao Bian, Qinghua Hu, Changqing Zhang
2024	J	`jnl`	UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation. CoRR Juzheng Zhang, Yatao Bian, Yongqiang Chen, Quanming Yao
2024	J	`jnl`	Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection. ACM Trans. Knowl. Discov. Data Yifan He, Yatao Bian, Xi Ding, Bingzhe Wu, Jihong Guan, Ji Zhang, Shuigeng Zhou
2024	—	`conf`	WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong
2023	J	`jnl`	Activity Cliff Prediction: Dataset and Benchmark. CoRR Ziqiao Zhang, Bangyi Zhao, Ailin Xie, Yatao Bian, Shuigeng Zhou
2023	A*	`conf`	BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. ICLR Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao
2023	A*	`conf`	Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. EMNLP Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
2023	J	`jnl`	Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. CoRR Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
2023	A*	`conf`	Curriculum Graph Poisoning. WWW Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu
2023	A*	`conf`	Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
2023	J	`jnl`	Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
2023	A*	`conf`	DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI 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
2023	J	`jnl`	ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking. CoRR Yiqiang Yi, Xu Wan, Yatao Bian, Le Ou-Yang, Peilin Zhao
2023	A*	`conf`	Fairness-guided Few-shot Prompting for Large Language Models. NeurIPS Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu
2023	J	`jnl`	Fairness-guided Few-shot Prompting for Large Language Models. CoRR Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu
2023	A*	`conf`	Learning Invariant Molecular Representation in Latent Discrete Space. NeurIPS Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang, Jingsong Lv, Hongyang Chen, Huajun Chen
2023	J	`jnl`	Learning Invariant Molecular Representation in Latent Discrete Space. CoRR Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang, Jingsong Lv, Hongyang Chen, Huajun Chen
2023	A*	`conf`	Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
2023	J	`jnl`	Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng
2023	—	`conf`	RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data. EMNLP (Findings) Haotian Wang, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, Bingzhe Wu
2023	J	`jnl`	Rethinking and Simplifying Bootstrapped Graph Latents. CoRR Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
2023	J	`jnl`	Reweighted Mixup for Subpopulation Shift. CoRR Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao
2023	A	`conf`	SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
2023	J	`jnl`	SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
2023	A*	`conf`	Simplifying and Empowering Transformers for Large-Graph Representations. NeurIPS Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
2023	J	`jnl`	Simplifying and Empowering Transformers for Large-Graph Representations. CoRR Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
2023	J	`jnl`	SyNDock: N Rigid Protein Docking via Learnable Group Synchronization. CoRR Yuanfeng Ji, Yatao Bian, Guoji Fu, Peilin Zhao, Ping Luo
2023	J	`jnl`	Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
2023	A*	`conf`	Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
2023	J	`jnl`	X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong
2022	J	`jnl`	A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR 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
2022	J	`jnl`	Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery? CoRR Ziqiao Zhang, Yatao Bian, Ailin Xie, Pengju Han, Long-Kai Huang, Shuigeng Zhou
2022	J	`jnl`	Cross-dependent graph neural networks for molecular property prediction. Bioinform. Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang
2022	J	`jnl`	DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. CoRR Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang
2022	—	`conf`	Diversified Multiscale Graph Learning with Graph Self-Correction. TAG-ML Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong
2022	J	`jnl`	Diversity Boosted Learning for Domain Generalization with Large Number of Domains. CoRR Xi Leng, Xiaoying Tang, Yatao Bian
2022	A*	`conf`	Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media. WWW Erxue Min, Yu Rong, Yatao Bian, Tingyang Xu, Peilin Zhao, Junzhou Huang, Sophia Ananiadou
2022	J	`jnl`	DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR 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
2022	A*	`conf`	Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. ICLR Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
2022	A*	`conf`	Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport. IJCAI Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
2022	J	`jnl`	Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport. CoRR Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
2022	A*	`conf`	Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method. ACM Multimedia Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang, Yinglu Zhang, Jihong Guan, Yatao Bian, Shuigeng Zhou
2022	J	`jnl`	Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method. CoRR Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang, Yinglu Zhang, Jihong Guan, Yatao Bian, Shuigeng Zhou
2022	J	`jnl`	Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs. CoRR Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian
2022	J	`jnl`	ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR 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
2022	A*	`conf`	Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
2022	A*	`conf`	Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
2022	A*	`conf`	Learning Neural Set Functions Under the Optimal Subset Oracle. NeurIPS Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian
2022	J	`jnl`	Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. CoRR Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian
2022	J	`jnl`	Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction. CoRR Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Junzhou Huang, Da Luo, Kangyi Lin, Sophia Ananiadou
2022	—	`conf`	MoDNA: motif-oriented pre-training for DNA language model. BCB Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li, Junzhou Huang
2022	A*	`conf`	Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer. SIGIR Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao
2022	J	`jnl`	Pareto Invariant Risk Minimization. CoRR Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
2022	J	`jnl`	Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang
2022	J	`jnl`	Transformer for Graphs: An Overview from Architecture Perspective. CoRR Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong
2022	A*	`conf`	Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang
2022	A*	`conf`	UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao
2022	J	`jnl`	UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao
2022	A*	`conf`	p-Laplacian Based Graph Neural Networks. ICML Guoji Fu, Peilin Zhao, Yatao Bian
2021	J	`jnl`	Diversified Multiscale Graph Learning with Graph Self-Correction. CoRR Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang
2021	J	`jnl`	Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations. CoRR Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
2021	J	`jnl`	Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis. CoRR Bingzhe Wu, Zhicong Liang, Yatao Bian, Chaochao Chen, Junzhou Huang, Yuan Yao
2021	A*	`conf`	Graph Information Bottleneck for Subgraph Recognition. ICLR Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
2021	J	`jnl`	Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. CoRR Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
2021	A*	`conf`	Not All Low-Pass Filters are Robust in Graph Convolutional Networks. NeurIPS Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu
2021	A*	`conf`	On Self-Distilling Graph Neural Network. IJCAI Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang
2021	J	`jnl`	Recognizing Predictive Substructures with Subgraph Information Bottleneck. CoRR Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
2021	J	`jnl`	p-Laplacian Based Graph Neural Networks. CoRR Guoji Fu, Peilin Zhao, Yatao Bian
2020	J	`jnl`	Continuous Submodular Function Maximization. CoRR Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	J	`jnl`	Dual Message Passing Neural Network for Molecular Property Prediction. CoRR Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang
2020	A*	`conf`	From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	J	`jnl`	From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. CoRR Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	J	`jnl`	GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data. CoRR Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
2020	J	`jnl`	Graph Information Bottleneck for Subgraph Recognition. CoRR Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
2020	J	`jnl`	On Self-Distilling Graph Neural Network. CoRR Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang
2020	A*	`conf`	Self-Supervised Graph Transformer on Large-Scale Molecular Data. NeurIPS Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
2019	—	`—`	Provable Non-Convex Optimization and Algorithm Validation via Submodularity. Yatao Bian
2016	J	`jnl`	Greedy MAXCUT Algorithms and their Information Content. CoRR Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
2016	Misc	`conf`	Information-theoretic analysis of MaxCut algorithms. ITA Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
2015	B	`conf`	Greedy MaxCut algorithms and their information content. ITW Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
2013	—	`conf`	Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression. ECML/PKDD (3) Yatao Bian, Xiong Li, Mingqi Cao, Yuncai Liu
2013	J	`jnl`	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 Jian Song, Yatao Bian, Junchi Yan, Xu Zhao, Yuncai Liu
2012	B	`conf`	Parallelized Annealed Particle Filter for real-time marker-less motion tracking via heterogeneous computing. ICPR Yatao Bian, Xu Zhao, Jian Song, Yuncai Liu