Hongkai Zheng

According to our database, Hongkai Zheng authored at least 12 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

A Double-Node-Upset Tolerant Latch for Enhanced Reliability in Radiation-Prone Environments.

Zijie Gong, Jilong Zhang, Hongkai Zheng, Fuyuan Lang, Boyun Zhang, Yan Li, Xiaoyang Zeng

Proceedings of the IEEE International Symposium on Circuits and Systems, 2026

2025

LSRS: Latent Scale Rejection Sampling for Visual Autoregressive Modeling.

Hongkai Zheng, Piji Li

CoRR, December, 2025

Group-Wise Optimization for Self-Extensible Codebooks in Vector Quantized Models.

Hongkai Zheng, Piji Li

CoRR, October, 2025

Advancing End-to-End Pixel Space Generative Modeling via Self-supervised Pre-training.

Jiachen Lei, Keli Liu, Julius Berner, Haiming Yu, Hongkai Zheng, Jiahong Wu, Xiangxiang Chu

CoRR, October, 2025

Blade: A Derivative-free Bayesian Inversion Method using Diffusion Priors.

Hongkai Zheng, Austin Wang, Zihui Wu, Zhengyu Huang, Ricardo Baptista, Yisong Yue

CoRR, October, 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

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, Nikola Borislavov Kovachki, Zachary E. Ross, Katherine L. Bouman, Yisong Yue

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Fast Training of Diffusion Models with Masked Transformers.

Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar

Trans. Mach. Learn. Res., 2024

2023

Fast Sampling of Diffusion Models via Operator Learning.

Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the International Conference on Machine Learning, 2023

2022

Langevin Monte Carlo for Contextual Bandits.

Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar

Proceedings of the International Conference on Machine Learning, 2022

2021

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

2020

Implicit competitive regularization in GANs.

Florian Schäfer, Hongkai Zheng, Animashree Anandkumar

Proceedings of the 37th International Conference on Machine Learning, 2020