Toward an AI Physicist for Unsupervised Learning

24 October 2018

Papers citing "Toward an AI Physicist for Unsupervised Learning"

29 / 29 papers shown

Title
Oracle-Preserving Latent Flows Alexander Roman Roy T. Forestano Konstantin T. Matchev Katia Matcheva Eyup B. Unlu DRL 34 5 0 02 Feb 2023
Automated Gadget Discovery in Science Lea M. Trenkwalder Andrea López-Incera Hendrik Poulsen Nautrup Fulvio Flamini H. Briegel 15 3 0 24 Dec 2022
Microscopy is All You Need Sergei V. Kalinin Rama K Vasudevan Yongtao Liu Ayana Ghosh Kevin M. Roccapriore M. Ziatdinov 28 0 0 12 Oct 2022
Neuronal diversity can improve machine learning for physics and beyond A. Choudhary Anil Radhakrishnan J. Lindner S. Sinha W. Ditto AI4CE 24 3 0 09 Apr 2022
AI Research Associate for Early-Stage Scientific Discovery M. Behandish J. Maxwell Johan de Kleer AI4CE 18 1 0 02 Feb 2022
Machine-Learning Non-Conservative Dynamics for New-Physics Detection Ziming Liu Bohan Wang Qi Meng Wei Chen M. Tegmark Tie-Yan Liu PINN AI4CE 14 15 0 31 May 2021
Learning Hamiltonian dynamics by reservoir computer Han Zhang Huawei Fan Liang Wang Xingang Wang 6 3 0 24 Apr 2021
Similarity-Based Equational Inference in Physics Jordan Meadows André Freitas 11 5 0 24 Mar 2021
Toward Building Science Discovery Machines A. Khalili A. Bouchachia AI4CE 19 1 0 24 Mar 2021
Discovering conservation laws from trajectories via machine learning Seungwoong Ha Hawoong Jeong PINN AI4CE 21 10 0 08 Feb 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
Probabilistic Grammars for Equation Discovery Jure Brence L. Todorovski S. Džeroski 4 34 0 01 Dec 2020
Forecasting Hamiltonian dynamics without canonical coordinates A. Choudhary J. Lindner Elliott G. Holliday Scott T. Miller S. Sinha W. Ditto 4 26 0 28 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
The world as a neural network V. Vanchurin 20 57 0 04 Aug 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 6 183 0 18 Jun 2020
Symbolic Pregression: Discovering Physical Laws from Distorted Video S. Udrescu Max Tegmark 21 40 0 19 May 2020
Boosting on the shoulders of giants in quantum device calibration A. Wozniakowski Jayne Thompson M. Gu F. Binder 14 3 0 13 May 2020
Renormalized Mutual Information for Artificial Scientific Discovery Leopoldo Sarra A. Aiello F. Marquardt 11 4 0 04 May 2020
Learning the Ising Model with Generative Neural Networks Francesco DÁngelo Lucas Böttcher AI4CE 16 28 0 15 Jan 2020
Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learning Tailin Wu 19 1 0 11 Jan 2020
Operationally meaningful representations of physical systems in neural networks Hendrik Poulsen Nautrup Tony Metger Raban Iten Sofiene Jerbi Lea M. Trenkwalder H. Wilming H. Briegel R. Renner AI4CE NAI 11 25 0 02 Jan 2020
Learning Generalized Quasi-Geostrophic Models Using Deep Neural Numerical Models Redouane Lguensat Julien Le Sommer Sammy Metref E. Cosme Ronan Fablet AI4Cl AI4CE 7 6 0 20 Nov 2019
Exploration and Exploitation in Symbolic Regression using Quality-Diversity and Evolutionary Strategies Algorithms Jean-Philippe Bruneton L. Cazenille A. Douin V. Reverdy 11 5 0 10 Jun 2019
AI Feynman: a Physics-Inspired Method for Symbolic Regression S. Udrescu Max Tegmark 22 844 0 27 May 2019
Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction P. Watson AI4Cl AI4CE 27 63 0 24 Apr 2019
Fast Neural Network Predictions from Constrained Aerodynamics Datasets Cristina White D. Ushizima C. Farhat AI4CE 11 18 0 26 Jan 2019
Discovering physical concepts with neural networks Raban Iten Tony Metger H. Wilming L. D. Rio R. Renner PINN AI4CE 19 384 0 26 Jul 2018
Building machines that adapt and compute like brains Brenden M. Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 890 0 11 Nov 2017