
Deep ensembles exhibit emergent equivariance through data augmentation, as proven by neural tangent kernel theory.


coremsg

Emergent-Equivariance-in-Deep-Ensembles-Theory-and-Experiments


Emergent Equivariance in Deep Ensembles: Theory and Experiments


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This paper introduces Lie Algebra Canonicalization (LieLAC), a novel method for achieving equivariance in pre-trained neural networks by transforming inputs to a canonical form, leveraging Lie group theory to enhance performance in image classification and PDE solving tasks.


lie-algebra-canonicalization-achieving-equivariance-in-pre-trained-neural-networks-for-image-classification-and-pde-solvers


Lie Algebra Canonicalization: Achieving Equivariance in Pre-trained Neural Networks for Image Classification and PDE Solvers
