This repository collects and organizes academic papers on equivariant neural networks, a branch of deep learning concerned with building invariance or equivariance to symmetry groups (rotations, permutations, etc.) into network architectures. The list covers foundational papers like Group Equivariant CNNs and Steerable CNNs, spanning theory, group convolutions, density estimation, and applications across computer vision and scientific computing.