Approximately Equivariant Networks for Imperfectly Symmetric Dynamics

28 January 2022

Papers citing "Approximately Equivariant Networks for Imperfectly Symmetric Dynamics"

23 / 23 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
Relaxed Equivariance via Multitask Learning Ahmed A. A. Elhag T. Konstantin Rusch Francesco Di Giovanni Michael Bronstein 44 2 0 23 Oct 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 44 2 0 18 Sep 2024
Symmetry constrained neural networks for detection and localization of damage in metal plates James Amarel Christopher Rudolf Athanasios P. Iliopoulos J. Michopoulos Leslie N. Smith 34 0 0 09 Sep 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 39 4 0 23 Aug 2024
Deep reinforcement learning with symmetric data augmentation applied for aircraft lateral attitude tracking control Yifei Li E. Kampen 32 0 0 13 Jul 2024
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts Hyunsu Kim Yegon Kim Hongseok Yang Juho Lee 37 0 0 05 Jul 2024
Morphological Symmetries in Robotics Daniel Felipe Ordoñez Apraez Giulio Turrisi Vladimir Kostic Mario Martin Antonio Agudo Francesc Moreno-Noguer Massimiliano Pontil Claudio Semini Carlos Mastalli AI4CE 37 6 0 23 Feb 2024
Equivariant Symmetry Breaking Sets YuQing Xie Tess E. Smidt 25 4 0 05 Feb 2024
Entropy Transformer Networks: A Learning Approach via Tangent Bundle Data Manifold Pourya Shamsolmoali Masoumeh Zareapoor 33 1 0 24 Jul 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 35 22 0 27 May 2023
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 27 13 0 03 Nov 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 27 88 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 26 73 0 14 Oct 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons Serge Assaad Carlton Downey Rami Al-Rfou Nigamaa Nayakanti Benjamin Sapp 36 17 0 08 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
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 64 0 02 Jul 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 76 185 0 19 Apr 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 205 2,282 0 18 Oct 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 422 0 10 Mar 2020
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 159 308 0 05 Nov 2018