Yifei Wang

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Yisen WangAssistant Professor, Peking UniversityVerified email at pku.edu.cn
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung ResearchVerified email at pku.edu.cn
Zeming WeiUndergraduate, Peking UniversityVerified email at stu.pku.edu.cn
Tianqi DuPhD Student, Peking UniversityVerified email at pku.edu.cn
Qi ChenPeking UniversityVerified email at pku.edu.cn
Zhengyang GengPhD student, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Mingjie LiPostdoc Researcher, CISPAVerified email at pku.edu.cn
Dongxian WuBytedanceVerified email at bytedance.com
Yichuan MoPh.D. Student, Peking UniversityVerified email at stu.pku.edu.cn
Weiran HuangAssociate Professor, Shanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Rundong LuoUndergraduate Student, Peking UniversityVerified email at stu.pku.edu.cn
Jingyi CuiPeking UniversityVerified email at stu.pku.edu.cn
Chawin SitawarinPostdoctoral Researcher @ MetaVerified email at meta.com
Lin LiPh.D. student, King's College LondonVerified email at kcl.ac.uk
Michael SpratlingUniversity of Luxembourg and King's College LondonVerified email at kcl.ac.uk
Jiangyan MaPeking UniversityVerified email at stu.pku.edu.cn
Zhenguo LiHuawei Noah's Ark LabVerified email at huawei.com
Jingtong SuPh.D. Student, New York UniversityVerified email at nyu.edu
Shiji XinHarvard UniversityVerified email at g.harvard.edu
Zidi XiongUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu

Yifei Wang

Other names王一飞

Postdoc, MIT

Verified email at mit.edu - Homepage

Machine Learning Self-supervised Learning Adversarial Learning Graph Neural Networks


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap Y Wang, Q Zhang, Y Wang, J Yang, Z Lin ICLR 2022, 2022	100	2022
Dissecting the diffusion process in linear graph convolutional networks Y Wang, Y Wang, J Yang, Z Lin NeurIPS 2021, 2021	60	2021
Jailbreak and guard aligned language models with only few in-context demonstrations Z Wei, Y Wang, Y Wang arXiv preprint arXiv:2310.06387, 2023	43	2023
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders Q Zhang, Y Wang, Y Wang NeurIPS 2022 Spotlight, 2022	32	2022
Residual relaxation for multi-view representation learning Y Wang, Z Geng, F Jiang, C Li, Y Wang, J Yang, Z Lin NeurIPS 2021, 2021	30	2021
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Y Mo, D Wu, Y Wang, Y Guo, Y Wang NeurIPS 2022 Spotlight, 2022	29	2022
Optimization-induced graph implicit nonlinear diffusion Q Chen, Y Wang, Y Wang, J Yang, Z Lin ICML 2022, 2022	28	2022
CFA: Class-wise Calibrated Fair Adversarial Training Z Wei, Y Wang, Y Guo, Y Wang CVPR 2023, 2023	25	2023
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond X Guo, Y Wang, T Du, Y Wang ICLR 2023, 2023	21	2023
G CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters M Li, X Guo, Y Wang, Y Wang, Z Lin ICML 2022, 2022	18	2022
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism Z Zhuo, Y Wang, J Ma, Y Wang ICLR 2023, 2023	14	2023
A Message Passing Perspective on Learning Dynamics of Contrastive Learning Y Wang, Q Zhang, T Du, J Yang, Z Lin, Y Wang ICLR 2023, 2023	11	2023
Fooling Adversarial Training with Inducing Noise Z Wang, Y Wang, Y Wang arXiv preprint arXiv:2111.10130, 2021	9	2021
Rethinking Weak Supervision in Helping Contrastive Learning J Cui, W Huang, Y Wang*, Y Wang ICML 2023, 2023	8	2023
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning R Luo, Y Wang, Y Wang ICLR 2023, 2023	8	2023
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Q Wang, Y Wang, H Zhu, Y Wang NeurIPS 2022 Spotlight, 2022	8	2022
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training Y Wang, Y Wang, J Yang, Z Lin ICLR 2022, 2022	8	2022
Train once, and decode as you like C Tian, Y Wang, H Cheng, Y Lian, Z Zhang COLING 2020, 2020	7	2020
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Y Wang, L Li, J Yang, Z Lin, Y Wang NeurIPS 2023, 2023	5	2023
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States M Li, Y Wang, Y Wang, Z Lin ICLR 2023, 2023	5	2023

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