Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks

9 March 2020

Papers citing "Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks"

22 / 22 papers shown

Title
Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space Vinicius Hernandes Thomas Spriggs Saqar Khaleefah E. Greplova 52 1 0 21 Mar 2025
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients Zakaria Patel S. J. Wetzel 25 2 0 09 Sep 2024
The R-mAtrIx Net Shailesh Lal Suvajit Majumder E. Sobko 24 5 0 14 Apr 2023
Fluctuation based interpretable analysis scheme for quantum many-body snapshots Henning Schlomer A. Bohrdt 24 4 0 12 Apr 2023
Discovering Sparse Representations of Lie Groups with Machine Learning Roy T. Forestano Konstantin T. Matchev Katia Matcheva Alexander Roman Eyup B. Unlu Sarunas Verner 35 10 0 10 Feb 2023
Oracle-Preserving Latent Flows Alexander Roman Roy T. Forestano Konstantin T. Matchev Katia Matcheva Eyup B. Unlu DRL 44 5 0 02 Feb 2023
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles Roy T. Forestano Konstantin T. Matchev Katia Matcheva Alexander Roman Eyup B. Unlu Sarunas Verner AI4CE 36 22 0 13 Jan 2023
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 40 2 0 17 Oct 2022
Discovering Conservation Laws using Optimal Transport and Manifold Learning Peter Y. Lu Rumen Dangovski M. Soljavcić 27 17 0 31 Aug 2022
Learning quantum symmetries with interactive quantum-classical variational algorithms Jonathan Z. Lu R. A. Bravo Kaiying Hou Gebremedhin A. Dagnew S. Yelin K. Najafi 40 3 0 23 Jun 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 37 84 0 13 Apr 2022
On scientific understanding with artificial intelligence Mario Krenn R. Pollice S. Guo Matteo Aldeghi Alba Cervera-Lierta ... Florian Hase A. Jinich AkshatKumar Nigam Zhenpeng Yao Alán Aspuru-Guzik 37 186 0 04 Apr 2022
AI Poincaré 2.0: Machine Learning Conservation Laws from Differential Equations Ziming Liu Varun Madhavan M. Tegmark PINN 38 27 0 23 Mar 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks Y. Yasuda R. Onishi 27 6 0 22 Feb 2022
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 75 27 0 06 Dec 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 32 17 0 15 Oct 2021
Discovering conservation laws from trajectories via machine learning Seungwoong Ha Hawoong Jeong PINN AI4CE 26 10 0 08 Feb 2021
Twin Neural Network Regression S. J. Wetzel Kevin Ryczko R. Melko Isaac Tamblyn UQCV 28 11 0 29 Dec 2020
Scientific intuition inspired by machine learning generated hypotheses Pascal Friederich Mario Krenn Isaac Tamblyn Alán Aspuru-Guzik AI4CE 24 34 0 27 Oct 2020
Detecting Symmetries with Neural Networks Sven Krippendorf Marc Syvaeri 23 61 0 30 Mar 2020
Entanglement-guided architectures of machine learning by quantum tensor network Yuhan Liu Xiao Zhang M. Lewenstein Shi-Ju Ran 28 32 0 24 Mar 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017