Data Augmentation and Regularization for Learning Group Equivariance

Code

• github.com/usinedepain/eq_aug_reg_release
  Officialpytorch★ 0

Abstract

In many machine learning tasks, known symmetries can be used as an inductive bias to improve model performance. In this paper, we consider learning group equivariance through training with data augmentation. We summarize results from a previous paper of our own, and extend the results to show that equivariance of the trained model can be achieved through training on augmented data in tandem with regularization.

Tasks

Reproductions