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ORCIDYifei Wang 0001
Person information
- affiliation: Peking University, School of Mathematical Sciences, China
Other persons with the same name
- Yifei Wang (aka: Yi-fei Wang, Yi-Fei Wang) — disambiguation page
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2020 – today
- 2024
[i29]Yifei Wang, Jizhe Zhang, Yisen Wang:
Do Generated Data Always Help Contrastive Learning? CoRR abs/2403.12448 (2024)- [i28]Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang:
Non-negative Contrastive Learning. CoRR abs/2403.12459 (2024) - 2023
- [j1]Qi Chen
, Yifei Wang, Zhengyang Geng, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Equilibrium Image Denoising With Implicit Differentiation. IEEE Trans. Image Process. 32: 1868-1881 (2023) - [c25]Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang:
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization. AAAI 2023: 10519-10527 - [c24]Zeming Wei, Yifei Wang, Yiwen Guo, Yisen Wang:
CFA: Class-Wise Calibrated Fair Adversarial Training. CVPR 2023: 8193-8201 - [c23]Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. ICLR 2023 - [c22]Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang:
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond. ICLR 2023 - [c21]Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin:
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States. ICLR 2023 - [c20]Rundong Luo, Yifei Wang, Yisen Wang:
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning. ICLR 2023 - [c19]Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang:
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism. ICLR 2023 - [c18]Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang:
Rethinking Weak Supervision in Helping Contrastive Learning. ICML 2023: 6448-6467 - [c17]Qi Zhang, Yifei Wang, Yisen Wang:
On the Generalization of Multi-modal Contrastive Learning. ICML 2023: 41677-41693 - [c16]Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang:
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning. NeurIPS 2023 - [c15]Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang:
Adversarial Examples Are Not Real Features. NeurIPS 2023 - [c14]George Ma, Yifei Wang, Yisen Wang:
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. NeurIPS 2023 - [c13]Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. NeurIPS 2023 - [c12]Qi Zhang, Yifei Wang, Yisen Wang:
Identifiable Contrastive Learning with Automatic Feature Importance Discovery. NeurIPS 2023 - [i27]Rundong Luo, Yifei Wang, Yisen Wang:
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning. CoRR abs/2303.01289 (2023) - [i26]Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang:
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism. CoRR abs/2303.02387 (2023) - [i25]Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. CoRR abs/2303.04435 (2023) - [i24]Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang:
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond. CoRR abs/2303.06562 (2023) - [i23]Zeming Wei, Yifei Wang, Yiwen Guo, Yisen Wang:
CFA: Class-wise Calibrated Fair Adversarial Training. CoRR abs/2303.14460 (2023) - [i22]Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang:
Rethinking Weak Supervision in Helping Contrastive Learning. CoRR abs/2306.04160 (2023) - [i21]Qi Zhang, Yifei Wang, Yisen Wang:
On the Generalization of Multi-modal Contrastive Learning. CoRR abs/2306.04272 (2023) - [i20]Hong Zhu, Runpeng Yu, Xing Tang, Yifei Wang, Yuan Fang, Yisen Wang:
Robust Long-Tailed Learning via Label-Aware Bounded CVaR. CoRR abs/2308.15405 (2023) - [i19]Zeming Wei, Yifei Wang, Yisen Wang:
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations. CoRR abs/2310.06387 (2023) - [i18]Chen Liu, Hongyu Zang, Xin Li, Yong Heng, Yifei Wang, Zhen Fang, Yisen Wang, Mingzhong Wang:
Towards Control-Centric Representations in Reinforcement Learning from Images. CoRR abs/2310.16655 (2023) - [i17]Jiangyan Ma, Yifei Wang, Yisen Wang:
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. CoRR abs/2310.18716 (2023) - [i16]Qi Zhang, Yifei Wang, Yisen Wang:
Identifiable Contrastive Learning with Automatic Feature Importance Discovery. CoRR abs/2310.18904 (2023) - [i15]Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang:
Adversarial Examples Are Not Real Features. CoRR abs/2310.18936 (2023) - [i14]Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. CoRR abs/2310.19360 (2023) - [i13]Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang:
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning. CoRR abs/2311.02687 (2023) - 2022
- [c11]Qi Chen, Yifei Wang, Yisen Wang, Jianlong Chang, Qi Tian, Jiansheng Yang, Zhouchen Lin:
Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium. IEEE Big Data 2022: 864-873 - [c10]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. ICLR 2022 - [c9]Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. ICLR 2022 - [c8]Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Optimization-Induced Graph Implicit Nonlinear Diffusion. ICML 2022: 3648-3661 - [c7]Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin:
G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters. ICML 2022: 12782-12796 - [c6]Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang:
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. NeurIPS 2022 - [c5]Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang:
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors. NeurIPS 2022 - [c4]Qi Zhang, Yifei Wang, Yisen Wang:
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. NeurIPS 2022 - [i12]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. CoRR abs/2203.13455 (2022) - [i11]Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. CoRR abs/2203.13457 (2022) - [i10]Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Optimization-Induced Graph Implicit Nonlinear Diffusion. CoRR abs/2206.14418 (2022) - [i9]Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang:
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors. CoRR abs/2210.06807 (2022) - [i8]Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang:
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. CoRR abs/2210.07540 (2022) - [i7]Qi Zhang, Yifei Wang, Yisen Wang:
How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. CoRR abs/2210.08344 (2022) - [i6]Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang:
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization. CoRR abs/2212.09082 (2022) - 2021
- [c3]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. NeurIPS 2021: 5758-5769 - [c2]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. NeurIPS 2021: 12104-12115 - [c1]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. ECML/PKDD (3) 2021: 494-509 - [i5]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. CoRR abs/2102.10739 (2021) - [i4]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. CoRR abs/2107.00352 (2021) - [i3]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. CoRR abs/2110.15348 (2021) - [i2]Zhirui Wang, Yifei Wang, Yisen Wang:
Fooling Adversarial Training with Inducing Noise. CoRR abs/2111.10130 (2021) - 2020
- [i1]Yifei Wang, Dan Peng, Furui Liu, Zhenguo Li, Zhitang Chen, Jiansheng Yang:
Decoder-free Robustness Disentanglement without (Additional) Supervision. CoRR abs/2007.01356 (2020)
Coauthor Index
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