Provably Strict Generalisation Benefit for Equivariant Models

20 February 2021

Papers citing "Provably Strict Generalisation Benefit for Equivariant Models"

25 / 25 papers shown

Title
Learning with Exact Invariances in Polynomial Time Ashkan Soleymani B. Tahmasebi Stefanie Jegelka P. Jaillet 78 0 0 27 Feb 2025
Data Augmentation and Regularization for Learning Group Equivariance Oskar Nordenfors Axel Flinth 57 0 0 10 Feb 2025
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 42 4 0 23 Aug 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 50 2 0 30 May 2024
Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning? Linfeng Zhao Owen Howell Jung Yeon Park Xu Zhu Robin G. Walters Lawson L. S. Wong 36 1 0 17 Jul 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 35 22 0 27 May 2023
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 29 6 0 26 May 2023
Optimization Dynamics of Equivariant and Augmented Neural Networks Axel Flinth F. Ohlsson 41 5 0 23 Mar 2023
Deep Neural Networks with Efficient Guaranteed Invariances M. Rath A. P. Condurache 16 4 0 02 Mar 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 47 63 0 30 Jan 2023
VC dimensions of group convolutional neural networks P. Petersen A. Sepliarskaia VLM 27 7 0 19 Dec 2022
Invariant Lipschitz Bandits: A Side Observation Approach Nam-Phuong Tran Long Tran-Thanh 47 1 0 14 Dec 2022
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi Marc Finzi Sanyam Kapoor Andres Potapczynski Micah Goldblum A. Wilson BDL MLT AI4CE 29 51 0 24 Nov 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi Gabriele Cesa Taco S. Cohen 56 17 0 24 Oct 2022
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 35 2 0 17 Oct 2022
Theory for Equivariant Quantum Neural Networks Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 40 89 0 16 Oct 2022
Representation Theory for Geometric Quantum Machine Learning Michael Ragone Paolo Braccia Quynh T. Nguyen Louis Schatzki Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo AI4CE 28 73 0 14 Oct 2022
$Image to Icosahedral Projection for $\mathrm{SO}(3)$ Object Reasoning from Single-View Images$ Image to Icosahedral Projection for $\mathrm{SO}(3)$ Object Reasoning from Single-View Images David M. Klee Ondrej Biza Robert W. Platt Robin G. Walters 26 4 0 18 Jul 2022
A Theory of PAC Learnability under Transformation Invariances Hang Shao Omar Montasser Avrim Blum 21 18 0 15 Feb 2022
Residual Pathway Priors for Soft Equivariance Constraints Marc Finzi Gregory W. Benton A. Wilson BDL UQCV 24 50 0 02 Dec 2021
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi Cengiz Pehlevan 18 5 0 14 Oct 2021
Implicit Bias of Linear Equivariant Networks Hannah Lawrence Kristian Georgiev A. Dienes B. Kiani AI4CE 40 14 0 12 Oct 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 27 36 0 11 Oct 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 308 0 05 Nov 2018