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A Unified Contrastive Energy-based Model for Understanding the
  Generative Ability of Adversarial Training

A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training

25 March 2022
Yifei Wang
Yisen Wang
Jiansheng Yang
Zhouchen Lin
    AAML
ArXivPDFHTML

Papers citing "A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training"

4 / 4 papers shown
Title
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from
  a Minimax Game Perspective
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Yifei Wang
Liangchen Li
Jiansheng Yang
Zhouchen Lin
Yisen Wang
23
11
0
30 Oct 2023
Exploring the Connection between Robust and Generative Models
Exploring the Connection between Robust and Generative Models
Senad Beadini
I. Masi
AAML
24
1
0
08 Apr 2023
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
194
345
0
15 Dec 2021
Learning Energy-Based Models With Adversarial Training
Learning Energy-Based Models With Adversarial Training
Xuwang Yin
Shiying Li
Gustavo K. Rohde
AAML
DiffM
33
9
0
11 Dec 2020
1