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cs.LG2025
To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking
Hannah Lawrence, Elyssa Hofgard, Vasco Portilheiro +3
Symmetry-aware methods for machine learning, such as data augmentation and equivariant architectures, encourage correct model behavior on all transformations (e.g. rotations or per…
cs.LG2024
Relaxed Equivariant Graph Neural Networks
Elyssa Hofgard, Rui Wang, Robin Walters +1
3D Euclidean symmetry equivariant neural networks have demonstrated notable success in modeling complex physical systems. We introduce a framework for relaxed graph equivari…