activity
20242026
most citedImproving Diffusion Inverse Problem Solving with Decoupled Noise Annealing

18 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer

Wenda Chu, Bingliang Zhang, Jiaqi Han +4

Autoregressive image modeling relies on visual tokenizers to compress images into compact latent representations. We design an end-to-end training pipeline that jointly optimizes r…

cs.CV2025

STeP: A Framework for Solving Scientific Video Inverse Problems with Spatiotemporal Diffusion Priors

Bingliang Zhang, Zihui Wu, Berthy T. Feng +3

Reconstructing spatially and temporally coherent videos from time-varying measurements is a fundamental challenge in many scientific domains. A major difficulty arises from the spa…

cs.LG2025★ 1 cited

InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences

Hongkai Zheng, Wenda Chu, Bingliang Zhang +9

Plug-and-play diffusion priors (PnPDP) have emerged as a promising research direction for solving inverse problems. However, current studies primarily focus on natural image restor…

cs.LG2024★ 18 cited

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing

Bingliang Zhang, Wenda Chu, Julius Berner +3

Diffusion models have recently achieved success in solving Bayesian inverse problems with learned data priors. Current methods build on top of the diffusion sampling process, where…

eess.IV2024★ 2 cited

Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors

Zihui Wu, Yu Sun, Yifan Chen +3

Diffusion models (DMs) have recently shown outstanding capabilities in modeling complex image distributions, making them expressive image priors for solving Bayesian inverse proble…