2 papers
cs.LG2024
Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward
Zhiwei Jia, Yuesong Nan, Huixi Zhao +1
Recent research has shown that fine-tuning diffusion models (DMs) with arbitrary rewards, including non-differentiable ones, is feasible with reinforcement learning (RL) techniques…
eess.IV2020
AHP-Net: adaptive-hyper-parameter deep learning based image reconstruction method for multilevel low-dose CT
Qiaoqiao Ding, Yuesong Nan, Hao Gao +1
Low-dose CT (LDCT) imaging is desirable in many clinical applications to reduce X-ray radiation dose to patients. Inspired by deep learning (DL), a recent promising direction of mo…