Berthelot, David

9 publications

ICML 2025 Mechanisms of Projective Composition of Diffusion Models Arwen Bradley, Preetum Nakkiran, David Berthelot, James Thornton, Joshua M. Susskind

ICML 2025 Normalizing Flows Are Capable Generative Models Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Navdeep Jaitly, Joshua M. Susskind

NeurIPS 2025 STARFlow: Scaling Latent Normalizing Flows for High-Resolution Image Synthesis Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Ángel Bautista, Joshua M. Susskind, Shuangfei Zhai

NeurIPS 2025 TADA: Improved Diffusion Sampling with Training-Free Augmented DynAmics Tianrong Chen, Huangjie Zheng, David Berthelot, Jiatao Gu, Joshua M. Susskind, Shuangfei Zhai

ICLR 2022 AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alexey Kurakin

NeurIPS 2020 FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin A Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li

ICLR 2020 ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel

NeurIPS 2019 MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, Colin A Raffel

ICLR 2019 Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer David Berthelot, Colin Raffel, Aurko Roy, Ian Goodfellow