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2003.04299
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Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks
Physical Review Research (PRResearch), 2020
9 March 2020
Zakaria Patel
R. Melko
Joseph Scott
Maysum Panju
Vijay Ganesh
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Papers citing
"Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks"
39 / 39 papers shown
Towards autonomous quantum physics research using LLM agents with access to intelligent tools
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Uncovering Emergent Physics Representations Learned In-Context by Large Language Models
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Jaeyong Bae
Dong-Kyum Kim
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AI4CE
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124
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17 Aug 2025
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
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434
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30 Mar 2025
Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space
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Thomas Spriggs
Saqar Khaleefah
E. Greplova
462
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21 Mar 2025
Deep Learning based discovery of Integrable Systems
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Suvajit Majumder
E. Sobko
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13 Mar 2025
Learning finite symmetry groups of dynamical systems via equivariance detection
Pablo Calvo-Barlés
Sergio G. Rodrigo
Luis Martín-Moreno
297
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04 Mar 2025
Data-Driven Discovery of Conservation Laws from Trajectories via Neural Deflation
Communications in nonlinear science & numerical simulation (CNSNS), 2024
Shaoxuan Chen
Panayotis G. Kevrekidis
Hong-Kun Zhang
Wei Zhu
PINN
292
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07 Oct 2024
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients
S. J. Wetzel
Zakaria Patel
559
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09 Sep 2024
KAN 2.0: Kolmogorov-Arnold Networks Meet Science
Ziming Liu
Pingchuan Ma
Yixuan Wang
Wojciech Matusik
Max Tegmark
470
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19 Aug 2024
Closed-Form Interpretation of Neural Network Classifiers with Symbolic Regression Gradients
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337
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10 Jan 2024
A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data
Mechanical systems and signal processing (MSSP), 2023
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Souvik Chakraborty
191
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10 Oct 2023
Identifying the Group-Theoretic Structure of Machine-Learned Symmetries
Physics Letters B (Phys. Lett. B), 2023
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
277
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14 Sep 2023
Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments
Tareq Jaouni
Sören Arlt
Carlos Ruiz-Gonzalez
Ebrahim Karimi
Xuemei Gu
Mario Krenn
GNN
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13 Sep 2023
Discovering New Interpretable Conservation Laws as Sparse Invariants
Ziming Liu
Patrick Obin Sturm
Saketh Bharadwaj
Sam Silva
M. Tegmark
183
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31 May 2023
Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl
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02 May 2023
The R-mAtrIx Net
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Suvajit Majumder
E. Sobko
195
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14 Apr 2023
Fluctuation based interpretable analysis scheme for quantum many-body snapshots
SciPost Physics (SciPost Phys.), 2023
Henning Schlomer
A. Bohrdt
330
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12 Apr 2023
Discovering Sparse Representations of Lie Groups with Machine Learning
Physics Letters B (Phys. Lett. B), 2023
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
265
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10 Feb 2023
Oracle-Preserving Latent Flows
Alexander Roman
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Eyup B. Unlu
DRL
313
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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
304
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13 Jan 2023
Quantum Similarity Testing with Convolutional Neural Networks
Physical Review Letters (PRL), 2022
Yadong Wu
Yan Zhu
Ge Bai
Yuexuan Wang
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368
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A tradeoff between universality of equivariant models and learnability of symmetries
Vasco Portilheiro
288
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Discovering Conservation Laws using Optimal Transport and Manifold Learning
Nature Communications (Nat Commun), 2022
Peter Y. Lu
Rumen Dangovski
M. Soljavcić
315
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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
198
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23 Jun 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic
Mechanical systems and signal processing (MSSP), 2022
Barbara Z Cunha
C. Droz
A. Zine
Stéphane Foulard
M. Ichchou
AI4CE
264
134
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13 Apr 2022
On scientific understanding with artificial intelligence
Nature Reviews Physics (Nat. Rev. Phys.), 2022
Mario Krenn
R. Pollice
S. Guo
Matteo Aldeghi
Alba Cervera-Lierta
...
Florian Hase
A. Jinich
AkshatKumar Nigam
Zhenpeng Yao
Alán Aspuru-Guzik
321
282
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04 Apr 2022
AI Poincaré 2.0: Machine Learning Conservation Laws from Differential Equations
Physical Review E (Phys. Rev. E), 2022
Ziming Liu
Varun Madhavan
M. Tegmark
PINN
331
35
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23 Mar 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks
APL Machine Learning (AML), 2022
Y. Yasuda
R. Onishi
442
7
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22 Feb 2022
Noether Networks: Meta-Learning Useful Conserved Quantities
Neural Information Processing Systems (NeurIPS), 2021
Ferran Alet
Dylan D. Doblar
Allan Zhou
J. Tenenbaum
Kenji Kawaguchi
Chelsea Finn
279
31
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
240
25
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15 Oct 2021
Improving Simulations with Symmetry Control Neural Networks
Marc Syvaeri
Sven Krippendorf
AI4CE
137
1
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29 Apr 2021
Variational Autoencoder Analysis of Ising Model Statistical Distributions and Phase Transitions
D. Yevick
DRL
279
7
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13 Apr 2021
Discovering conservation laws from trajectories via machine learning
Seungwoong Ha
Hawoong Jeong
PINN
AI4CE
260
11
0
08 Feb 2021
Twin Neural Network Regression
Applied AI Letters (AA), 2020
Zakaria Patel
Kevin Ryczko
R. Melko
Isaac Tamblyn
UQCV
384
15
0
29 Dec 2020
Scientific intuition inspired by machine learning generated hypotheses
Pascal Friederich
Mario Krenn
Isaac Tamblyn
Alán Aspuru-Guzik
AI4CE
333
41
0
27 Oct 2020
Boosting on the shoulders of giants in quantum device calibration
A. Wozniakowski
Jayne Thompson
M. Gu
F. Binder
203
5
0
13 May 2020
Detecting Symmetries with Neural Networks
Sven Krippendorf
Marc Syvaeri
228
70
0
30 Mar 2020
Entanglement-guided architectures of machine learning by quantum tensor network
Yuhan Liu
Xiao Zhang
M. Lewenstein
Shi-Ju Ran
304
35
0
24 Mar 2018
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