257 citations · 320 across the 6 of their papers we have counts for
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cs.LG2021
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers
Gabriele Prato, Simon Guiroy, Ethan Caballero +2
Empirical science of neural scaling laws is a rapidly growing area of significant importance to the future of machine learning, particularly in the light of recent breakthroughs ac…
cs.LG2021★ 44 cited
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Kartik Ahuja, Ethan Caballero, Dinghuai Zhang +4
The invariance principle from causality is at the heart of notable approaches such as invariant risk minimization (IRM) that seek to address out-of-distribution (OOD) generalizatio…