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AI Feynman: a Physics-Inspired Method for Symbolic Regression

27 May 2019

Papers citing "AI Feynman: a Physics-Inspired Method for Symbolic Regression"

44 / 344 papers shown

Title
Encoding physics to learn reaction-diffusion processes Chengping Rao Pu Ren Qi Wang O. Buyukozturk Haoqin Sun Yang Liu PINN AI4CE DiffM 105 97 0 09 Jun 2021
Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos Lele Luan Yang Liu Hao Sun PINN AI4CE 43 0 0 09 Jun 2021
Physical Constraint Embedded Neural Networks for inference and noise regulation Gregory Barber Mulugeta Haile Tzikang Chen PINN 32 1 0 19 May 2021
Automated Biodesign Engineering by Abductive Meta-Interpretive Learning Wang-Zhou Dai Liam Hallett Stephen Muggleton Geoff S. Baldwin AI4CE 11 0 0 17 May 2021
Informed Equation Learning M. Werner Andrej Junginger Philipp Hennig Georg Martius 56 14 0 13 May 2021
Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 121 39 0 03 May 2021
Data-driven discovery of Green's functions with human-understandable deep learning Nicolas Boullé Christopher Earls Alex Townsend PINN AI4CE 60 60 0 01 May 2021
Distilling Wikipedia mathematical knowledge into neural network models J. Kim Mikel Landajuela Brenden K. Petersen 69 9 0 13 Apr 2021
An Approach to Symbolic Regression Using Feyn Kevin René Brolos Meera Machado C. Cave Jaan Kasak Valdemar Stentoft-Hansen Victor Galindo Batanero T. Jelen Casper Wilstrup 44 45 0 12 Apr 2021
Shape-constrained Symbolic Regression -- Improving Extrapolation with Prior Knowledge G. Kronberger F. O. França Bogdan Burlacu C. Haider M. Kommenda 71 48 0 29 Mar 2021
Symbolic regression outperforms other models for small data sets Casper Wilstrup Jaan Kasak 49 28 0 28 Mar 2021
Similarity-Based Equational Inference in Physics Jordan Meadows André Freitas 43 5 0 24 Mar 2021
Toward Building Science Discovery Machines A. Khalili A. Bouchachia AI4CE 25 1 0 24 Mar 2021
Symmetry meets AI G. Barenboim J. Hirn V. Sanz 65 22 0 10 Mar 2021
Identifying Physical Law of Hamiltonian Systems via Meta-Learning Seungjun Lee Haesang Yang W. Seong 61 13 0 23 Feb 2021
Data-driven formulation of natural laws by recursive-LASSO-based symbolic regression Yuma Iwasaki M. Ishida 18 3 0 18 Feb 2021
Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics Jongeun Kim S. Leyffer Prasanna Balaprakash 40 3 0 16 Feb 2021
A Primer for Neural Arithmetic Logic Modules Bhumika Mistry K. Farrahi Jonathon S. Hare 33 8 0 23 Jan 2021
Machine-Learning Mathematical Structures Yang-Hui He 70 41 0 15 Jan 2021
Learning Symbolic Expressions via Gumbel-Max Equation Learner Networks Gang Chen 40 9 0 12 Dec 2020
Disentangling a Deep Learned Volume Formula J. Craven Vishnu Jejjala Arjun Kar 74 19 0 07 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 90 121 0 03 Dec 2020
Probabilistic Grammars for Equation Discovery Jure Brence L. Todorovski Jannis Brugger 48 34 0 01 Dec 2020
Conjecturing-Based Discovery of Patterns in Data J. Brooks David J. Edwards Craig E. Larson N. Van Cleemput 14 1 0 23 Nov 2020
Symbolically Solving Partial Differential Equations using Deep Learning Maysum Panju Kourosh Parand A. Ghodsi 70 4 0 12 Nov 2020
A Neuro-Symbolic Method for Solving Differential and Functional Equations Maysum Panju A. Ghodsi 32 2 0 04 Nov 2020
Forecasting Hamiltonian dynamics without canonical coordinates A. Choudhary J. Lindner Elliott G. Holliday Scott T. Miller S. Sinha W. Ditto 65 26 0 28 Oct 2020
Logic Guided Genetic Algorithms D. Ashok Joseph Scott S. J. Wetzel Maysum Panju Vijay Ganesh 108 12 0 21 Oct 2020
Maximum Reward Formulation In Reinforcement Learning S. Gottipati Yashaswi Pathak Rohan Nuttall Sahir Raviteja Chunduru Ahmed Touati Sriram Ganapathi Subramanian Matthew E. Taylor Sarath Chandar 113 14 0 08 Oct 2020
OccamNet: A Fast Neural Model for Symbolic Regression at Scale Owen Dugan Rumen Dangovski Allan dos Santos Costa Samuel Kim Pawan Goyal J. Jacobson M. Soljavcić 95 11 0 16 Jul 2020
The Computational Limits of Deep Learning Neil C. Thompson Kristjan Greenewald Keeheon Lee Gabriel F. Manso VLM 91 531 0 10 Jul 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 60 168 0 22 Jun 2020
Discovering Symbolic Models from Deep Learning with Inductive Biases M. Cranmer Alvaro Sanchez-Gonzalez Peter W. Battaglia Rui Xu Kyle Cranmer D. Spergel S. Ho AI4CE 96 483 0 19 Jun 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 120 193 0 18 Jun 2020
Symbolic Regression using Mixed-Integer Nonlinear Optimization V. Austel Cristina Cornelio S. Dash Joao Goncalves L. Horesh Tyler R. Josephson N. Megiddo 51 5 0 11 Jun 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 88 31 0 10 Jun 2020
Symbolic Pregression: Discovering Physical Laws from Distorted Video S. Udrescu Max Tegmark 96 41 0 19 May 2020
Boosting on the shoulders of giants in quantum device calibration A. Wozniakowski Jayne Thompson M. Gu F. Binder 38 3 0 13 May 2020
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence Hamidreza Eivazi L. Guastoni P. Schlatter Hossein Azizpour Ricardo Vinuesa AI4CE 60 7 0 01 May 2020
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations Marko Durasevic D. Jakobović M. Martins S. Picek Markus Wagner 24 10 0 27 Apr 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 156 414 0 10 Mar 2020
Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks S. J. Wetzel R. Melko Joseph Scott Maysum Panju Vijay Ganesh 73 70 0 09 Mar 2020
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients Brenden K. Petersen Mikel Landajuela T. Nathan Mundhenk Claudio Santiago Soo K. Kim Joanne T. Kim 68 320 0 10 Dec 2019
Symbolic Regression Methods for Reinforcement Learning Jiří Kubalík Erik Derner J. Žegklitz Robert Babuška OffRL 47 24 0 22 Mar 2019