36 citations · 37 across the 3 of their papers we have counts for
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cs.LG2024
Understanding and Improving Training-free Loss-based Diffusion Guidance
Yifei Shen, Xinyang Jiang, Yezhen Wang +3
Adding additional control to pretrained diffusion models has become an increasingly popular research area, with extensive applications in computer vision, reinforcement learning, a…
cs.LG2021★ 1 cited
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Yezhen Wang, Bo Li, Tong Che +3
Confidence calibration is of great importance to the reliability of decisions made by machine learning systems. However, discriminative classifiers based on deep neural networks ar…
cs.LG2020
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
Bo Li, Yezhen Wang, Shanghang Zhang +4
The success of supervised learning hinges on the assumption that the training and test data come from the same underlying distribution, which is often not valid in practice due to…