Symbolic regression

This page was last updated on 2025-08-18 06:12:54 UTC

Manually curated articles on Symbolic regression

Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations
visibility_off Discovering governing equations from data by sparse identification of nonlinear dynamical systems S. Brunton, J. Proctor, J. Kutz 2015-09-11 Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences of the United States of America 4023 72 open_in_new
visibility_off Robust learning from noisy, incomplete, high-dimensional experimental data via physically constrained symbolic regression Patrick A. K. Reinbold, Logan Kageorge, M. Schatz, R. Grigoriev 2021-02-24 Nature Communications 114 25 open_in_new
visibility_off Data-driven discovery of coordinates and governing equations Kathleen P. Champion, Bethany Lusch, J. Kutz, S. Brunton 2019-03-29 Proceedings of the National Academy of Sciences of the United States of America 781 72 open_in_new
visibility_off Chaos as an intermittently forced linear system S. Brunton, Bingni W. Brunton, J. Proctor, E. Kaiser, J. Kutz 2016-08-18 Nature Communications 535 72 open_in_new
visibility_off Sparse identification of nonlinear dynamics for model predictive control in the low-data limit E. Kaiser, J. Kutz, S. Brunton 2017-11-15 Proceedings. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 538 72 open_in_new
visibility_off Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics N. Mangan, S. Brunton, J. Proctor, J. Kutz 2016-05-26 IEEE Transactions on Molecular, Biological and Multi-Scale Communications, IEEE Transactions on Molecular Biological and Multi-Scale Communications 366 72 open_in_new
visibility_off SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics Kadierdan Kaheman, J. Kutz, S. Brunton 2020-04-05 Proceedings. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 286 72 open_in_new
visibility_off Multidimensional Approximation of Nonlinear Dynamical Systems Patrick Gelß, Stefan Klus, J. Eisert, Christof Schutte 2018-09-07 Journal of Computational and Nonlinear Dynamics 72 22 open_in_new
visibility_off Learning Discrepancy Models From Experimental Data Kadierdan Kaheman, E. Kaiser, B. Strom, J. Kutz, S. Brunton 2019-09-18 ArXiv, arXiv.org 46 72 open_in_new
visibility_off Discovery of Physics From Data: Universal Laws and Discrepancies Brian M. de Silva, D. Higdon, S. Brunton, J. Kutz 2019-06-19 Frontiers in Artificial Intelligence 88 72 open_in_new
visibility_off Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control Urban Fasel, J. Kutz, Bingni W. Brunton, S. Brunton 2021-11-22 Proceedings. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 251 72 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 48 96 open_in_new
visibility_off A Unified Framework for Sparse Relaxed Regularized Regression: SR3 P. Zheng, T. Askham, S. Brunton, J. Kutz, A. Aravkin 2018-07-14 IEEE Access 145 72 open_in_new
Abstract Title Authors Publication Date Journal/ Conference Citation count Highest h-index View recommendations

Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index
visibility_off SINDy on slow manifolds Diemen Delgado-Cano, Erick Kracht, Urban Fasel, Benjamin Herrmann 2025-07-01 ArXiv 0 12
visibility_off Discovering Governing Equations in the Presence of Uncertainty Ridwan Olabiyi, Han Hu, Ashif Iquebal 2025-07-13 ArXiv 0 1
visibility_off Efficient data-driven regression for reduced-order modeling of spatial pattern formation Alessandro Alla, Rudy Geelen, Hannah Lu 2025-08-09 ArXiv 0 0
visibility_off Sparse identification of nonlinear dynamics with library optimization mechanism: Recursive long-term prediction perspective Ansei Yonezawa, Heisei Yonezawa, S. Yahagi, Itsuro Kajiwara, Shinya Kijimoto, Hikaru Taniuchi, Kentaro Murakami 2025-07-24 ArXiv 0 10
visibility_off Discovering Interpretable Ordinary Differential Equations from Noisy Data Rahul Golder, M. M. F. Hasan 2025-07-29 ArXiv 0 0
visibility_off Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics Wei Liu, Kiran Bacsa, Loon Ching Tang, Eleni N. Chatzi 2025-06-22 ArXiv 0 5
visibility_off ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized partial differential equations from sparse and noisy data Aviral Prakash, Ben S. Southworth, M. Klasky 2025-06-23 ArXiv 0 2
visibility_off Sparse Identification of Nonlinear Dynamics with Conformal Prediction Urban Fasel 2025-07-15 ArXiv 0 12
visibility_off Scientific Machine Learning of Chaotic Systems Discovers Governing Equations for Neural Populations Anthony G. Chesebro, David Hofmann, Vaibhav Dixit, Earl K. Miller, Richard Granger, Alan Edelman, Christopher Rackauckas, L. Mujica-Parodi, H. Strey 2025-07-04 ArXiv 0 23
visibility_off Overcoming error-in-variable problem in data-driven model discovery by orthogonal distance regression Lloyd Fung 2025-07-31 ArXiv 0 0
visibility_off Causal Operator Discovery in Partial Differential Equations via Counterfactual Physics-Informed Neural Networks Ronald Katende 2025-06-25 ArXiv 0 0
visibility_off Time-series modeling with neural flow maps Bingxian Xu, Zoey E. Ho, Yitong Huang 2025-06-24 bioRxiv 0 1
visibility_off Evaluating PDE discovery methods for multiscale modeling of biological signals Andréa Ducos, Audrey Denizot, Thomas Guyet, Hugues Berry 2025-06-25 ArXiv 0 5
visibility_off Learning Structured Population Models from Data with WSINDy Rainey Lyons, Vanja Dukic, David M. Bortz 2025-06-30 ArXiv 1 2
visibility_off Neural Dynamic Modes: Computational Imaging of Dynamical Systems from Sparse Observations Ali SaraerToosi, Renbo Tu, K. Azizzadenesheli, A. Levis 2025-07-03 ArXiv 0 37
visibility_off Robust PDE discovery under sparse and highly noisy conditions via attention neural networks Shilin Zhang, Yunqing Huang, Nianyu Yi, shihan Zhang 2025-06-21 ArXiv 0 16
visibility_off Data-Driven Stabilisation of Unstable Periodic Orbits of the Three-Body Problem Owen M. Brook, J. Bramburger, Davide Amato, Urban Fasel 2025-07-11 ArXiv 0 12
visibility_off Sparse Identification of Nonlinear Dynamics for Stochastic Delay Differential Equations Dimitri Breda, D. Conte, Raffaele D'Ambrosio, Ida Santaniello, Muhammad Tanveer 2025-08-05 ArXiv 0 22
visibility_off Machine Learning-Based Nonlinear Nudging for Chaotic Dynamical Systems Jaemin Oh, Jinsil Lee, Youngjoon Hong 2025-08-07 ArXiv 0 3
visibility_off Blending data and physics for reduced-order modeling of systems with spatiotemporal chaotic dynamics Alex Guo, Michael D. Graham 2025-07-21 ArXiv 0 0
visibility_off Weak Form Scientific Machine Learning: Test Function Construction for System Identification April Tran, David M. Bortz 2025-07-03 ArXiv 0 4
visibility_off Characterizing control between interacting subsystems with deep Jacobian estimation Adam J. Eisen, Mitchell Ostrow, Sarthak Chandra, L. Kozachkov, Earl K. Miller, I. Fiete 2025-07-02 ArXiv 0 32
visibility_off Data-Driven Reconstruction and Characterization of Stochastic Dynamics via Dynamical Mode Decomposition Adva Baratz, L. M. Cangemi, A. Hamo, S. Refaely-Abramson, Amikam Levy 2025-07-08 ArXiv 0 30
visibility_off Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations Eva van Tegelen, George van Voorn, Ioannis Athanasiadis, P. Heijster 2025-07-25 ArXiv 0 15
visibility_off PhysicsCorrect: A Training-Free Approach for Stable Neural PDE Simulations Xinquan Huang, P. Perdikaris 2025-07-02 ArXiv 0 50
visibility_off Symmetry-reduced model reduction of shift-equivariant systems via operator inference Yu Shuai, Clarence W. Rowley 2025-07-24 ArXiv 0 0
visibility_off Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models Xinghao Dong, Huchen Yang, Jin-Long Wu 2025-06-25 ArXiv 1 1
visibility_off Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty A. Hubin 2025-07-09 ArXiv 0 9
visibility_off Quantum-Informed Machine Learning for Chaotic Systems Maida Wang, Xiao Xue, Peter V. Coveney 2025-07-26 ArXiv 0 4
visibility_off PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models Yongquan Qu, Matthieu Blanke, S. Shamekh, Pierre Gentine 2025-08-01 ArXiv 0 6
visibility_off PINN-Obs: Physics-Informed Neural Network-Based Observer for Nonlinear Dynamical Systems Ayoub Farkane, Mohamed Boutayeb, Mustapha Oudani, Mounir Ghogho 2025-07-09 ArXiv 0 7
visibility_off Forecasting chaotic dynamic using hybrid system Michele Baia, T. Matteuzzi, Franco Bagnoli 2025-07-21 ArXiv 0 2
visibility_off Neural models of multiscale systems: conceptual limitations, stochastic parametrizations, and a climate application Fabrizio Falasca 2025-06-27 ArXiv 0 1
visibility_off Simulating Three-dimensional Turbulence with Physics-informed Neural Networks Sifan Wang, Shyam Sankaran, P. Stinis, P. Perdikaris 2025-07-11 ArXiv 0 50
visibility_off Real-time prediction of plasma instabilities with sparse-grid-accelerated optimized dynamic mode decomposition Kevin Gill, Ionut-Gabriel Farcas, Silke Glas, Benjamin J. Faber 2025-07-03 ArXiv 0 9
visibility_off Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling Haley Rosso, Lars Ruthotto, K. Sargsyan 2025-07-29 ArXiv 0 27
visibility_off Structural System Identification via Validation and Adaptation Cristian López, Keegan J. Moore 2025-06-25 ArXiv 0 3
visibility_off Learning Koopman Models From Data Under General Noise Conditions Lucian-Cristian Iacob, M'at'e Sz'ecsi, G. Beintema, M. Schoukens, Roland T'oth 2025-07-13 ArXiv 1 7
visibility_off A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions Toan Huynh, Ruth Fajardo, Guannan Zhang, Lili Ju, Feng Bao 2025-08-09 ArXiv 0 5
visibility_off Physical Informed Neural Networks for modeling ocean pollutant Karishma Battina, Prathamesh Dinesh Joshi, R. Dandekar, R. Dandekar, S. Panat 2025-07-07 ArXiv 0 4
visibility_off Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Parametric Dynamical Systems Pantelis R. Vlachas, Konstantinos Vlachas, Eleni Chatzi 2025-06-24 ArXiv 0 5
visibility_off Inferring viscoplastic models from velocity fields: a physics-informed neural network approach Martin Lardy, Sham Tlili, Simon Gsell 2025-06-21 ArXiv 0 1
visibility_off Sparsity-Promoting Dynamic Mode Decomposition Applied to Sea Surface Temperature Fields Zhicheng Zhang, Yoshihiko Susuki, Atsushi Okazaki 2025-07-07 ArXiv 0 0
visibility_off When do World Models Successfully Learn Dynamical Systems? Edmund Ross, Claudia Drygala, Leonhard Schwarz, Samir Kaiser, F. D. Mare, Tobias Breiten, Hanno Gottschalk 2025-07-07 ArXiv 0 5
visibility_off GeoHNNs: Geometric Hamiltonian Neural Networks A. M. Aboussalah, Abdessalam Ed-dib 2025-07-21 ArXiv 0 4
visibility_off Learning Stochastic Multiscale Models Andrew F. Ilersich, Prasanth B. Nair 2025-06-27 ArXiv 0 0
visibility_off Forecasting Continuous Non-Conservative Dynamical Systems in SO(3) Lennart Bastian, Mohammad Rashed, N. Navab, Tolga Birdal 2025-08-11 ArXiv 0 54
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index