Machine learning and invariant theory

29 September 2022

Papers citing "Machine learning and invariant theory"

10 / 10 papers shown

Title
Prospective Learning: Learning for a Dynamic Future Ashwin De Silva Rahul Ramesh Rubing Yang Siyu Yu Joshua T. Vogelstein Pratik Chaudhari AI4TS 58 0 0 31 Oct 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 42 2 0 18 Sep 2024
Predicting the Thermal Sunyaev-Zel'dovich Field using Modular and Equivariant Set-Based Neural Networks L. Thiele M. Cranmer W. Coulton S. Ho D. Spergel 13 5 0 28 Feb 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics Rui Wang Robin G. Walters Rose Yu 25 73 0 28 Jan 2022
Implicit Bias of Linear Equivariant Networks Hannah Lawrence Kristian Georgiev A. Dienes B. Kiani AI4CE 30 14 0 12 Oct 2021
A simple equivariant machine learning method for dynamics based on scalars Weichi Yao Kate Storey-Fisher D. Hogg Soledad Villar AI4CE 35 9 0 07 Oct 2021
Invariant polynomials and machine learning W. Haddadin 32 7 0 26 Apr 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 188 1,229 0 08 Jan 2021
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 149 308 0 05 Nov 2018