Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups

25 October 2021

Papers citing "Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups"

9 / 9 papers shown

Title
Approximate Equivariance in Reinforcement Learning Jung Yeon Park Sujay Bhatt Sihan Zeng Lawson L. S. Wong Alec Koppel Sumitra Ganesh Robin Walters 34 1 0 06 Nov 2024
On the Fourier analysis in the SO(3) space : EquiLoPO Network Dmitrii Zhemchuzhnikov Sergei Grudinin 35 0 0 24 Apr 2024
Affine Invariance in Continuous-Domain Convolutional Neural Networks A. Mohaddes Johannes Lederer 23 1 0 13 Nov 2023
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras Tzu-Yuan Lin Minghan Zhu Maani Ghaffari 45 2 0 06 Oct 2023
An Exploration of Conditioning Methods in Graph Neural Networks Yeskendir Koishekenov Erik J. Bekkers AI4CE 37 3 0 03 May 2023
Towards a General Purpose CNN for Long Range Dependencies in $N$ D David W. Romero David M. Knigge Albert Gu Erik J. Bekkers E. Gavves Jakub M. Tomczak Mark Hoogendoorn 16 19 0 07 Jun 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho F. A. van der Ouderaa David W. Romero Mark van der Wilk 24 33 0 14 Apr 2022
Learning Partial Equivariances from Data David W. Romero Suhas Lohit 21 27 0 19 Oct 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 259 3,239 0 24 Nov 2016