Noether Networks: Meta-Learning Useful Conserved Quantities

6 December 2021

Papers citing "Noether Networks: Meta-Learning Useful Conserved Quantities"

24 / 24 papers shown

Title
Interpretable Machine Learning in Physics: A Review Sebastian Johann Wetzel Seungwoong Ha Raban Iten Miriam Klopotek Ziming Liu AI4CE 80 0 0 30 Mar 2025
Functional Risk Minimization Ferran Alet Clement Gehring Tomás Lozano-Pérez Kenji Kawaguchi Joshua B. Tenenbaum Leslie Pack Kaelbling OffRL 60 0 0 31 Dec 2024
Noether's razor: Learning Conserved Quantities Tycho F. A. van der Ouderaa Mark van der Wilk Pim de Haan 21 0 0 10 Oct 2024
SymmetryLens: A new candidate paradigm for unsupervised symmetry learning via locality and equivariance Onur Efe Arkadas Ozakin 29 0 0 07 Oct 2024
Learning equivariant tensor functions with applications to sparse vector recovery Wilson Gregory Josué Tonelli-Cueto Nicholas F. Marshall Andrew S. Lee Soledad Villar 39 1 0 03 Jun 2024
Analysis of the Identifying Regulation with Adversarial Surrogates Algorithm Ron Teichner Ron Meir Michael Margaliot 17 0 0 05 May 2024
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures Bruno Gavranovic Paul Lessard Andrew Dudzik Tamara von Glehn J. G. Araújo Petar Velickovic 32 8 0 23 Feb 2024
Understanding Learning through the Lens of Dynamical Invariants Alex Ushveridze 11 1 0 19 Jan 2024
Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example N. Evangelou Dimitrios G. Giovanis George A. Kevrekidis G. Pavliotis Ioannis G. Kevrekidis 11 0 0 29 Oct 2023
Neural Relational Inference with Fast Modular Meta-learning Ferran Alet Erica Weng Tomás Lozano Pérez L. Kaelbling 55 55 0 10 Oct 2023
Pseudo-Hamiltonian system identification Sigurd Holmsen Sølve Eidnes S. Riemer-Sørensen 18 3 0 09 May 2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 30 5 0 24 Apr 2023
Neural Algorithmic Reasoning with Causal Regularisation Beatrice Bevilacqua Kyriacos Nikiforou Borja Ibarz Ioana Bica Michela Paganini Charles Blundell Jovana Mitrović Petar Velivcković OOD CML NAI 36 26 0 20 Feb 2023
Generative Adversarial Symmetry Discovery Jianke Yang Robin G. Walters Nima Dehmamy Rose Yu GAN 19 22 0 01 Feb 2023
Unsupervised Learning of Equivariant Structure from Sequences Takeru Miyato Masanori Koyama Kenji Fukumizu 15 12 0 12 Oct 2022
FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities Takashi Matsubara Takaharu Yaguchi PINN 14 7 0 01 Oct 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
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 24 56 0 08 Apr 2022
Learning Partial Equivariances from Data David W. Romero Suhas Lohit 19 27 0 19 Oct 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
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 323 11,681 0 09 Mar 2017
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 438 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 278 1,400 0 01 Dec 2016