Discovering physical concepts with neural networks

26 July 2018

Papers citing "Discovering physical concepts with neural networks"

40 / 40 papers shown

Title
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia Jan van Gemert Daan Brinks Nergis Tömen 38 0 0 02 Oct 2024
KALE-LM: Unleash The Power Of AI For Science Via Knowledge And Logic Enhanced Large Model Weichen Dai Yezeng Chen Zijie Dai Zhijie Huang Yong-Jin Liu ... Chengli Zhong Xinhe Li Zeyu Wang Zhuoying Feng Yi Zhou 38 0 0 27 Sep 2024
Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients Zakaria Patel S. J. Wetzel 25 2 0 09 Sep 2024
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching Nan Jiang Md Nasim Yexiang Xue 39 0 0 02 Sep 2024
Vertical Symbolic Regression Nan Jiang Md Nasim Yexiang Xue 27 1 0 19 Dec 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 32 5 0 02 Feb 2023
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification A. Alberts Ilias Bilionis 34 12 0 18 Jan 2023
Data-aware customization of activation functions reduces neural network error Fuchang Gao Boyu Zhang 32 4 0 16 Jan 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 33 22 0 13 Jan 2023
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle Kinematics with Symbolic Regression Zhongtian Dong K. Kong Konstantin T. Matchev Katia Matcheva 46 13 0 15 Nov 2022
Improving aircraft performance using machine learning: a review S. L. Clainche E. Ferrer Sam Gibson Elisabeth Cross A. Parente Ricardo Vinuesa AI4CE 36 93 0 20 Oct 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video Florian Hofherr Lukas Koestler Florian Bernard Daniel Cremers AI4CE 37 10 0 29 Apr 2022
Machine learning for knowledge acquisition and accelerated inverse-design for non-Hermitian systems W. Ahmed M. Farhat K. Staliūnas Xiangliang Zhang Ying Wu 27 8 0 28 Apr 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 35 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 33 186 0 04 Apr 2022
SELFIES and the future of molecular string representations Mario Krenn Qianxiang Ai Senja Barthel Nessa Carson Angelo Frei ... Andrew Wang Andrew D. White Adamo Young Rose Yu A. Aspuru‐Guzik 35 149 0 31 Mar 2022
Flexible learning of quantum states with generative query neural networks Yan Zhu Yadong Wu Ge Bai Dongsheng Wang Yuexuan Wang G. Chiribella 29 35 0 14 Feb 2022
Neural Information Squeezer for Causal Emergence Jiang Zhang Kaiwei Liu CML 30 14 0 25 Jan 2022
Solving time dependent Fokker-Planck equations via temporal normalizing flow Xiaodong Feng Li Zeng Tao Zhou AI4CE 36 25 0 28 Dec 2021
SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits Eyal Rozenberg Aviv Karnieli O. Yesharim Joshua Foley-Comer Sivan Trajtenberg‐Mills Daniel Freedman A. Bronstein A. Arie 43 0 0 11 Dec 2021
Learning Continuous Face Representation with Explicit Functions Liping Zhang Weijun Li Linjun Sun Lina Yu X. Ning Xiaoli Dong Jian Xu Hong Qin CVBM 19 0 0 25 Oct 2021
Learning quantum dynamics with latent neural ODEs M. Choi Daniel Flam-Shepherd T. Kyaw A. Aspuru‐Guzik BDL AI4CE 32 5 0 20 Oct 2021
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Hamidreza Eivazi S. L. C. Martínez S. Hoyas Ricardo Vinuesa 33 92 0 03 Sep 2021
Revisiting Citizen Science Through the Lens of Hybrid Intelligence J. Rafner M. Gajdacz Gitte Kragh A. Hjorth A. Gander ... J. Miller Dominik Dellerman M. Haklay Pietro Michelucci J. Sherson 16 13 0 30 Apr 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 39 68 0 11 Apr 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 30 25 0 25 Feb 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
Deep learning insights into cosmological structure formation Luisa Lucie-Smith H. Peiris A. Pontzen Brian D. Nord Jeyan Thiyagalingam 24 6 0 20 Nov 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
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
Convolutional-network models to predict wall-bounded turbulence from wall quantities L. Guastoni A. Güemes A. Ianiro S. Discetti P. Schlatter Hossein Azizpour R. Vinuesa 28 167 0 22 Jun 2020
Computer-inspired Quantum Experiments Mario Krenn Manuel Erhard A. Zeilinger 27 73 0 23 Feb 2020
Learning models of quantum systems from experiments Antonio A. Gentile Brian Flynn S. Knauer N. Wiebe S. Paesani C. Granade J. Rarity R. Santagati A. Laing 8 57 0 14 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 313 0 07 Feb 2020
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning Peter Y. Lu Samuel Kim Marin Soljacic AI4CE 22 59 0 13 Jul 2019
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation Mario Krenn Florian Hase AkshatKumar Nigam Pascal Friederich Alán Aspuru-Guzik 13 70 0 31 May 2019
Optimizing Quantum Error Correction Codes with Reinforcement Learning Hendrik Poulsen Nautrup Nicolas Delfosse Vedran Dunjko H. Briegel N. Friis 14 155 0 20 Dec 2018
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 280 1,401 0 01 Dec 2016