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cs.LG2026
Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks
Ya-Wei Eileen Lin, Ron Levie
Canonicalization is a widely used strategy in equivariant machine learning, enforcing symmetry in neural networks by mapping each input to a standard form. Yet, it often introduces…
cs.LG2026
LieAugmenter: Equivariant Learning by Discovering Symmetries with Learnable Augmentations
Eduardo Santos-Escriche, Ya-Wei Eileen Lin, Stefanie Jegelka
Data augmentation is a powerful mechanism in equivariant machine learning, encouraging symmetry by training networks to produce consistent outputs under transformed inputs. Yet, ef…