70 citations · 93 across the 6 of their papers we have counts for
6 papers
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
David Berthelot, Arnaud Autef, Jierui Lin +6
Denoising Diffusion models have demonstrated their proficiency for generative sampling. However, generating good samples often requires many iterations. Consequently, techniques su…
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
Chuan Wen, Jianing Qian, Jierui Lin +3
Across applications spanning supervised classification and sequential control, deep learning has been reported to find "shortcut" solutions that fail catastrophically under minor c…
Keyframe-Focused Visual Imitation Learning
Chuan Wen, Jierui Lin, Jianing Qian +2
Imitation learning trains control policies by mimicking pre-recorded expert demonstrations. In partially observable settings, imitation policies must rely on observation histories,…
Fighting Copycat Agents in Behavioral Cloning from Observation Histories
Chuan Wen, Jierui Lin, Trevor Darrell +2
Imitation learning trains policies to map from input observations to the actions that an expert would choose. In this setting, distribution shift frequently exacerbates the effect…
3D Shape Reconstruction from Free-Hand Sketches
Jiayun Wang, Jierui Lin, Qian Yu +3
Sketches are the most abstract 2D representations of real-world objects. Although a sketch usually has geometrical distortion and lacks visual cues, humans can effortlessly envisio…
Free-riders in Federated Learning: Attacks and Defenses
Jierui Lin, Min Du, Jian Liu
Federated learning is a recently proposed paradigm that enables multiple clients to collaboratively train a joint model. It allows clients to train models locally, and leverages th…