Implicit competitive regularization in GANs. - Florian Schäfer; Hongkai Zheng; Animashree Anandkumar (ICML, 2020)

Physics-Informed Neural Operator for Learning Partial Differential Equations. - Zongyi Li; Hongkai Zheng; Nikola B. Kovachki; David Jin; Haoxuan Chen; Burigede Liu; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2021)

Langevin Monte Carlo for Contextual Bandits. - Pan Xu 002; Hongkai Zheng; Eric V. Mazumdar; Kamyar Azizzadenesheli; Animashree Anandkumar (ICML, 2022)

Fast Sampling of Diffusion Models via Operator Learning. - Hongkai Zheng; Weili Nie; Arash Vahdat; Kamyar Azizzadenesheli; Anima Anandkumar (ICML, 2023)

Fast Training of Diffusion Models with Masked Transformers. - Hongkai Zheng; Weili Nie; Arash Vahdat; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences. - Hongkai Zheng; Wenda Chu; Bingliang Zhang; Zihui Wu; Austin Wang; Berthy Feng; Caifeng Zou; Yu Sun 022; Nikola Borislavov Kovachki; Zachary E. Ross; Katherine L. Bouman; Yisong Yue (ICLR, 2025)

Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems. - Hongkai Zheng; Wenda Chu; Austin Wang; Nikola Borislavov Kovachki; Ricardo Baptista; Yisong Yue (Trans. Mach. Learn. Res., 2025)