Learning Invariances in Neural Networks

22 October 2020

Papers citing "Learning Invariances in Neural Networks"

21 / 21 papers shown

Title
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 65 1 0 20 Feb 2025
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 43 4 0 10 Aug 2024
Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries Alonso Urbano David W. Romero 35 2 0 19 Dec 2023
Amortised Invariance Learning for Contrastive Self-Supervision Ruchika Chavhan Henry Gouk Jan Stuehmer Calum Heggan Mehrdad Yaghoobi Timothy M. Hospedales SSL 40 11 0 24 Feb 2023
A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning Guozheng Ma Zhen Wang Zhecheng Yuan Xueqian Wang Bo Yuan Dacheng Tao OffRL 38 26 0 10 Oct 2022
On the Robustness and Anomaly Detection of Sparse Neural Networks Morgane Ayle Bertrand Charpentier John Rachwan Daniel Zügner Simon Geisler Stephan Günnemann AAML 55 3 0 09 Jul 2022
Warped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution Xinrui Zhan Yang Li Wenyu Liu Jianke Zhu 33 0 0 23 Jun 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho F. A. van der Ouderaa David W. Romero Mark van der Wilk 24 32 0 14 Apr 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 18 26 0 02 Apr 2022
On-Robot Learning With Equivariant Models Dian Wang Ming Jia Xu Zhu Robin Walters Robert W. Platt OffRL SSL 28 35 0 09 Mar 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 31 17 0 24 Feb 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 39 44 0 22 Feb 2022
Deep invariant networks with differentiable augmentation layers Cédric Rommel Thomas Moreau Alexandre Gramfort OOD 27 8 0 04 Feb 2022
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 75 26 0 06 Dec 2021
Residual Pathway Priors for Soft Equivariance Constraints Marc Finzi Gregory W. Benton A. Wilson BDL UQCV 24 51 0 02 Dec 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 78 81 0 15 Sep 2021
Topographic VAEs learn Equivariant Capsules Thomas Anderson Keller Max Welling BDL 44 38 0 03 Sep 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 32 37 0 10 Jun 2021
An Empirical Framework for Domain Generalization in Clinical Settings Haoran Zhang Natalie Dullerud Laleh Seyyed-Kalantari Q. Morris Shalmali Joshi Marzyeh Ghassemi OOD AI4CE 26 59 0 20 Mar 2021
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 309 0 05 Nov 2018
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 208 243 0 14 Jun 2018