6 citations · 15 across the 13 of their papers we have counts for
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How Good Are Deep Generative Models for Solving Inverse Problems?
Shichong Peng, Alireza Moazeni, Ke Li
Deep generative models, such as diffusion models, GANs, and IMLE, have shown impressive capability in tackling inverse problems. However, the validity of model-generated solutions…
Generating Unobserved Alternatives
Shichong Peng, Ke Li
We consider problems where multiple predictions can be considered correct, but only one of them is given as supervision. This setting differs from both the regression and class-con…
Better Knowledge Retention through Metric Learning
Ke Li, Shichong Peng, Kailas Vodrahalli +1
In continual learning, new categories may be introduced over time, and an ideal learning system should perform well on both the original categories and the new categories. While de…
Super-Resolution via Conditional Implicit Maximum Likelihood Estimation
Ke Li, Shichong Peng, Jitendra Malik
Single-image super-resolution (SISR) is a canonical problem with diverse applications. Leading methods like SRGAN produce images that contain various artifacts, such as high-freque…