E(2) Equivariant Neural Networks for Robust Galaxy Morphology Classification

1 code implementation • 2 Nov 2023 • Sneh Pandya, Purvik Patel, Franc O, Jonathan Blazek

We propose the use of group convolutional neural network architectures (GCNNs) equivariant to the 2D Euclidean group, $E(2)$, for the task of galaxy morphology classification by utilizing symmetries of the data present in galaxy images as an inductive bias in the architecture.

Inductive Bias Morphology classification