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cs.LG2025
Equivariance by Local Canonicalization: A Matter of Representation
Gerrit Gerhartz, Peter Lippmann, Fred A. Hamprecht
Equivariant neural networks offer strong inductive biases for learning from molecular and geometric data but often rely on specialized, computationally expensive tensor operations.…
cs.LG2025
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
Peter Lippmann, Gerrit Gerhartz, Roman Remme +1
In numerous applications of geometric deep learning, the studied systems exhibit spatial symmetries and it is desirable to enforce these. For the symmetry of global rotations and r…