137 citations · 348 across the 31 of their papers we have counts for
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cs.CV2021★ 3 cited
Grounding inductive biases in natural images:invariance stems from variations in data
Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos
To perform well on unseen and potentially out-of-distribution samples, it is desirable for machine learning models to have a predictable response with respect to transformations af…
cs.LG2021★ 5 cited
Addressing the Topological Defects of Disentanglement via Distributed Operators
Diane Bouchacourt, Mark Ibrahim, Stéphane Deny
A core challenge in Machine Learning is to learn to disentangle natural factors of variation in data (e.g. object shape vs. pose). A popular approach to disentanglement consists in…