Symbolic regression

This page was last updated on 2025-11-03 06:14:49 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 4250 74 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 122 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 825 74 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 563 74 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 567 74 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 376 74 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 298 74 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 74 24 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.org, ArXiv 47 74 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 92 74 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 272 74 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 54 97 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 151 74 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 Automatic Regression for Governing Equations with Control (ARGOSc) Amir Bahador Javadi, Amin Kargarian Marvasti, M. Naraghi-Pour 2025-09-11 ArXiv 0 20
visibility_off Data Denoising and Derivative Estimation for Data-Driven Modeling of Nonlinear Dynamical Systems Jiaqi Yao, Lewis Mitchell, John Maclean, Hemanth Saratchandran 2025-09-17 ArXiv 0 6
visibility_off Data-driven discovery of dynamical models in biology Bartosz Prokop, L. Gelens 2025-09-08 ArXiv 0 33
visibility_off MDBench: Benchmarking Data-Driven Methods for Model Discovery Amirmohammad Ziaei Bideh, Aleksandra Georgievska, Jonathan Gryak 2025-09-24 ArXiv 0 1
visibility_off Interpretable neural network system identification method for two families of second-order systems based on characteristic curves Federico J. Gonzalez, Luis P. Lara 2025-09-12 ArXiv 0 0
visibility_off Application of Reduced-Order Models for Temporal Multiscale Representations in the Prediction of Dynamical Systems Elias Al Ghazal, J. Mounayer, Beatriz Moya, Sebastian Rodriguez, C. Ghnatios, F. Chinesta 2025-10-21 ArXiv 0 15
visibility_off Data-driven Soliton Manifold Approximations for Dark and Bright Waves: Some Prototypical 1d Case Examples Su Yang, Shaoxuan Chen, Wei Zhu, Panayotis Kevrekidis 2025-10-15 ArXiv 0 1
visibility_off Unified Spatiotemporal Physics-Informed Learning (USPIL): A Framework for Modeling Complex Predator-Prey Dynamics Julian Evan Chrisnanto, Salsabila Rahma Alia, Y. H. Chrisnanto, Ferry Faizal 2025-09-16 ArXiv 0 2
visibility_off Latent Twins Matthias Chung, Deepanshu Verma, Max Collins, Amit N. Subrahmanya, V. Sastry, Vishwas Rao 2025-09-24 ArXiv 0 5
visibility_off PDE-Free Mass-Constrained Learning of Complex Systems with Hidden States: The crowd dynamics case Gianmaria Viola, Alessandro Della Pia, Lucia Russo, Ioannis G. Kevrekidis, Constantinos I. Siettos 2025-10-20 ArXiv 0 4
visibility_off A Novel Scientific Machine Learning Method for Epidemiological Modelling Tirtha Tilak Pani, R. Dandekar, Prathamesh Dinesh Joshi, R. Dandekar, S. Panat 2025-09-15 2025 IEEE International Conference on eScience (eScience) 0 5
visibility_off Solving inverse Gardner–Kawahara problems with physics-informed neural networks: a data-driven approach Mazaher Kabiri, Sanam Sabooni 2025-09-16 Physica Scripta 0 0
visibility_off Self-induced stochastic resonance: A physics-informed machine learning approach Divyesh Savaliya, Marius E. Yamakou 2025-10-26 ArXiv 0 10
visibility_off Towards Interpretable Deep Learning and Analysis of Dynamical Systems via the Discrete Empirical Interpolation Method Hojin Kim, R. Maulik 2025-10-22 ArXiv 0 26
visibility_off HYCO: Hybrid-Cooperative Learning for Data-Driven PDE Modeling Lorenzo Liverani, Matthys J. Steynberg, Enrique Zuazua 2025-09-17 ArXiv 1 2
visibility_off Data-Driven Discovery of Emergent Dynamics in Reaction-Diffusion Systems from Sparse and Noisy Observations Saumitra Dwivedi, Ricardo da Silva Torres, Ibrahim A. Hameed, Gunnar Tufte, Anniken Susanne T. Karlsen 2025-09-11 ArXiv 0 1
visibility_off Computation of simple invariant solutions in fluid turbulence with the aid of deep learning Jacob Page 2025-09-18 Nonlinear Dynamics 1 0
visibility_off Next-Generation Reservoir Computing for Dynamical Inference Rok Cestnik, E. A. Martens 2025-09-14 ArXiv 0 7
visibility_off Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators Gianluca Fabiani, Constantinos I. Siettos, Ioannis G. Kevrekidis 2025-09-28 ArXiv 0 9
visibility_off Data-Driven Reduced Modeling of Recurrent Neural Networks Alice Marraffa, Renate Krause, Valerio Mante, George Haller 2025-10-14 bioRxiv 0 0
visibility_off A multichannel generalization of the HAVOK method for the analysis of nonlinear dynamical systems Carlos Colchero, Jorge Perez, Alvaro Herrera, Oliver Probst 2025-09-16 ArXiv 0 0
visibility_off Leveraging Scale Separation and Stochastic Closure for Data-Driven Prediction of Chaotic Dynamics Ismaël Zighed, Nicolas Thome, Patrick Gallinari, T. Sayadi 2025-10-28 ArXiv 0 13
visibility_off Parameter Robustness in Data-Driven Estimation of Dynamical Systems Ayush Pandey 2025-09-08 ArXiv 0 0
visibility_off Data-efficient Kernel Methods for Learning Hamiltonian Systems Yasamin Jalalian, Mostafa Samir, Boumediene Hamzi, P. Tavallali, H. Owhadi 2025-09-21 ArXiv 0 38
visibility_off From Observations to Parameters: Detecting Changepoint in Nonlinear Dynamics with Simulation-based Inference Xiangbo Deng, Cheng Chen, Peng Yang 2025-10-20 ArXiv 0 1
visibility_off Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes Nicholas H. Nelsen, H. Owhadi, Andrew M. Stuart, Xianjin Yang, Zongren Zou 2025-10-07 ArXiv 0 38
visibility_off Data selection: at the interface of PDE-based inverse problem and randomized linear algebra Kathrin Hellmuth, Ruhui Jin, Qin Li, Stephen J. Wright 2025-10-02 ArXiv 0 2
visibility_off Learning to Solve Optimization Problems Constrained with Partial Differential Equations Yusuf Guven, Vincenzo Di Vito, Ferdinando Fioretto 2025-09-29 ArXiv 0 12
visibility_off Low-Rank Adaptation of Evolutionary Deep Neural Networks for Efficient Learning of Time-Dependent PDEs Jiahao Zhang, Shiheng Zhang, Guang Lin 2025-09-19 ArXiv 0 2
visibility_off Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data Luke McLennan, Yi Wang, R. Farell, Minh Nguyen, Chandrajit Bajaj 2025-09-08 ArXiv 0 3
visibility_off Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems Aleksandra Jekic, Afroditi Natsaridou, Signe Riemer-Sørensen, Helge Langseth, Odd Erik Gundersen 2025-09-24 ArXiv 0 17
visibility_off Physics-based deep kernel learning for parameter estimation in high dimensional PDEs Weihao Yan, Christoph Brune, Mengwu Guo 2025-09-17 ArXiv 0 1
visibility_off A novel approach to quantify out-of-distribution uncertainty in Neural and Universal Differential Equations Stefano Giampiccolo, Giovanni Iacca, Luca Marchetti 2025-10-03 bioRxiv 0 5
visibility_off Koopman Mode Decomposition of Thermodynamic Dissipation in Nonlinear Langevin Dynamics Daiki Sekizawa, Sosuke Ito, Masafumi Oizumi 2025-10-24 ArXiv 0 15
visibility_off Learning to Predict Chaos: Curriculum-Driven Training for Robust Forecasting of Chaotic Dynamics Harshil Vejendla 2025-10-05 ArXiv 0 0
visibility_off Control of dynamical systems with neural networks Lucas Bottcher 2025-10-06 ArXiv 0 0
visibility_off Statistical Parameter Calibration with the Generalized Fluctuation Dissipation Theorem and Generative Modeling L. T. Giorgini, Tobias Bischoff, Andre N. Souza 2025-09-24 ArXiv 1 7
visibility_off Equilibrium flow: From Snapshots to Dynamics Yanbo Zhang, Michael Levin 2025-09-22 ArXiv 0 3
visibility_off Machine Learning of Nonlinear Waves: Data-Driven Methods for Computer-Assisted Discovery of Equations, Symmetries, Conservation Laws, and Integrability J. Adriazola, Panayotis Kevrekidis, V. Koukouloyannis, Wei Zhu 2025-10-16 ArXiv 0 12
visibility_off An Adaptive CUR Algorithm and its Application to Reduced-Order Modeling of Random PDEs G. Palkar, H. Babaee 2025-09-25 ArXiv 0 4
visibility_off A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning Juan Diego Toscano, Daniel T. Chen, Vivek Oommen, Jérôme Darbon, G. Karniadakis 2025-09-17 ArXiv 1 9
visibility_off Dynamical system reconstruction from partial observations using stochastic dynamics Viktor Sip, Martin Breyton, S. Petkoski, V. Jirsa 2025-10-01 ArXiv 0 21
visibility_off A kernel-based approach to physics-informed nonlinear system identification Cesare Donati, Martina Mammarella, G. Calafiore, F. Dabbene, C. Lagoa, C. Novara 2025-09-09 ArXiv 0 40
visibility_off Neuro-Spectral Architectures for Causal Physics-Informed Networks Arthur Bizzi, Leonardo M. Moreira, M'arcio Marques, Leonardo Mendonça, Christian J'unior de Oliveira, Vitor Balestro, Lucas dos Santos Fernandez, Daniel Yukimura, Pavel Petrov, João M. Pereira, Tiago Novello, Lucas Nissenbaum 2025-09-05 ArXiv 1 8
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index