Fighting Fake News: Image Splice Detection via Learned Self-Consistency. - Minyoung Huh; Andrew Liu 001; Andrew Owens; Alexei A. Efros (ECCV (11), 2018)

Multi-view to Novel View: Synthesizing Novel Views With Self-learned Confidence. - Shao-Hua Sun; Minyoung Huh; Yuan-Hong Liao; Ning Zhang; Joseph J. Lim (ECCV (3), 2018)

Feedback Adversarial Learning: Spatial Feedback for Improving Generative Adversarial Networks. - Minyoung Huh; Shao-Hua Sun; Ning Zhang (CVPR, 2019)

Transforming and Projecting Images into Class-Conditional Generative Networks. - Minyoung Huh; Richard Zhang 001; Jun-Yan Zhu; Sylvain Paris; Aaron Hertzmann (ECCV (2), 2020)

Learning to Ground Multi-Agent Communication with Autoencoders. - Toru Lin; Minyoung Huh; Christopher Stauffer; Ser-Nam Lim; Phillip Isola (CoRR, 2021)

Totems: Physical Objects for Verifying Visual Integrity. - Jingwei Ma; Lucy Chai; Minyoung Huh; Tongzhou Wang 001; Ser-Nam Lim; Phillip Isola; Antonio Torralba 001 (ECCV (14), 2022)

Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. - Minyoung Huh; Brian Cheung; Pulkit Agrawal 001; Phillip Isola (ICML, 2023)

The Low-Rank Simplicity Bias in Deep Networks. - Minyoung Huh; Hossein Mobahi; Richard Zhang 001; Brian Cheung; Pulkit Agrawal 001; Phillip Isola (Trans. Mach. Learn. Res., 2023)

Position: The Platonic Representation Hypothesis. - Minyoung Huh; Brian Cheung; Tongzhou Wang 001; Phillip Isola (ICML, 2024)

Training Neural Networks from Scratch with Parallel Low-Rank Adapters. - Minyoung Huh; Brian Cheung; Jeremy Bernstein; Phillip Isola; Pulkit Agrawal 001 (CoRR, 2024)

The Platonic Representation Hypothesis. - Minyoung Huh; Brian Cheung; Tongzhou Wang 001; Phillip Isola (CoRR, 2024)

Scalable Optimization in the Modular Norm. - Tim Large; Yang Liu; Minyoung Huh; Hyojin Bahng; Phillip Isola; Jeremy Bernstein (CoRR, 2024)