7 citations · 11 across the 3 of their papers we have counts for
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cs.LG2022★ 3 cited
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
Cem Anil, Ashwini Pokle, Kaiqu Liang +5
Designing networks capable of attaining better performance with an increased inference budget is important to facilitate generalization to harder problem instances. Recent efforts…
cs.LG2022★ 7 cited
Deep Equilibrium Approaches to Diffusion Models
Ashwini Pokle, Zhengyang Geng, Zico Kolter
Diffusion-based generative models are extremely effective in generating high-quality images, with generated samples often surpassing the quality of those produced by other models u…
cs.LG2022★ 1 cited
Contrasting the landscape of contrastive and non-contrastive learning
Ashwini Pokle, Jinjin Tian, Yuchen Li +1
A lot of recent advances in unsupervised feature learning are based on designing features which are invariant under semantic data augmentations. A common way to do this is contrast…