Symbolic regression

This page was last updated on 2025-12-29 06:14:35 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 of the United States of America, Proceedings of the National Academy of Sciences 4443 77 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 125 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 870 77 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 584 77 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 600 77 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 392 77 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 312 77 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 78 26 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 50 77 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 96 77 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 292 77 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 58 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 160 77 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 attracting manifolds Diemen Delgado-Cano, Erick Kracht, Urban Fasel, Benjamin Herrmann 2025-12-04 Nonlinear Dynamics 0 13
visibility_off A joint optimization approach to identifying sparse dynamics using least squares kernel collocation Alexander W. Hsu, Ike W. Griss Salas, Jacob Stevens-Haas, J. N. Kutz, Aleksandr Y. Aravkin, Bamdad Hosseini 2025-11-23 ArXiv 0 29
visibility_off Information theory and discriminative sampling for model discovery Yuxuan Bao, J. N. Kutz 2025-12-17 ArXiv 0 3
visibility_off Discovering Power Grid Dynamics from Data Using Low-Rank Sparse Modeling Aiman Mushtaq Purra, Danish Rafiq 2025-12-05 ArXiv 0 7
visibility_off Adaptive backward stepwise selection of fast sparse identification of nonlinear dynamics Feng Jiang, Lin Du, Qing Xue, Zichen Deng, C. Grebogi 2025-11-29 Applied Mathematics and Mechanics 0 10
visibility_off Latent-Space Non-Linear Model Predictive Control for Partially-Observable Systems Luigi Marra, Onofrio Semeraro, Lionel Mathelin, Andrea Meil'an-Vila, Stefano Discetti 2025-11-24 ArXiv 0 16
visibility_off Differentiable Sparse Identification of Lagrangian Dynamics Zi-Rui Zhang, Hao Sun 2025-11-13 ArXiv 0 1
visibility_off Data-driven Interpretable Hybrid Robot Dynamics Christopher E. Mower, Rui Zong, Haitham Bou-Ammar 2025-12-10 ArXiv 0 29
visibility_off Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches S. Sivaranjani, Yuanyuan Shi, Nikolay Atanasov, T. Duong, Jie Feng, Tim Martin, Yuezhu Xu, Vijay Gupta, F. Allgower 2025-12-06 ArXiv 0 11
visibility_off A unified framework for equation discovery and dynamic prediction of hysteretic systems Siyuan Yang, Wei Liu, Zhilu Lai 2025-12-02 ArXiv 0 1
visibility_off Sparse identification of delay equations with distributed memory Dimitri Breda, Muhammad Tanveer, Jianhong Wu 2025-12-24 ArXiv 0 2
visibility_off GIMLET: Generalizable and Interpretable Model Learning through Embedded Thermodynamics Suguru Shiratori, Elham Kiyani, K. Shukla, G. Karniadakis 2025-12-22 ArXiv 0 18
visibility_off A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series Xuyang Li, J. Harlim, Dibyajyoti Chakraborty, R. Maulik 2025-11-10 ArXiv 0 27
visibility_off A Novel Reservoir Computing Framework for Chaotic Time Series Prediction Using Time Delay Embedding and Random Fourier Features S. Laha 2025-11-04 ArXiv 0 1
visibility_off Learning solution operator of dynamical systems with diffusion maps kernel ridge regression Jiwoo Song, Daning Huang, John Harlim 2025-12-19 ArXiv 0 2
visibility_off Rediscovering shallow water equations from experimental data Kjell S. Heinrich, Douglas S. Seth, Mats Ehrnstrom, S. Ellingsen 2025-11-07 ArXiv 0 18
visibility_off Spatially Aware Dictionary-Free Eigenfunction Identification for Modeling and Control of Nonlinear Dynamical Systems David Grasev 2025-11-27 ArXiv 0 2
visibility_off CODE: A global approach to ODE dynamics learning Nils Wildt, D. Tartakovsky, S. Oladyshkin, Wolfgang Nowak 2025-11-19 ArXiv 0 49
visibility_off Sparse Kalman Identification for Partially Observable Systems via Adaptive Bayesian Learning Jilan Mei, Tengjie Zheng, Lin Cheng, Sheng-hao Gong, Xu Huang 2025-11-22 ArXiv 0 6
visibility_off On the Effectiveness of Sparse Identification Methods to Detect Nonlinear Models of Oscillatory Dynamics in Psychology and the Life Sciences. Alessandro Maria Selvitella, Elliot Allen 2026-01-01 Nonlinear dynamics, psychology, and life sciences 0 0
visibility_off Variational Physics-Informed Ansatz for Reconstructing Hidden Interaction Networks from Steady States Kaiming Luo 2025-12-06 ArXiv 0 0
visibility_off Stable spectral neural operator for learning stiff PDE systems from limited data Rui Zhang, Han Wan, Yang Liu, Hao Sun 2025-12-12 ArXiv 0 6
visibility_off Degree-of-freedom and optimization-dynamic effects on the observability of Kuramoto-Sivashinsky systems Noah B. Frank, Joshua L. Pughe-Sanford, S. J. Grauer 2025-11-17 ArXiv 0 17
visibility_off ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees Andrea Goertzen, Sunbochen Tang, Navid Azizan 2025-12-01 ArXiv 0 1
visibility_off A Mechanistic Analysis of Transformers for Dynamical Systems Gregory Duth'e, N. Evangelou, Wei Liu, Ioannis G. Kevrekidis, Eleni N. Chatzi 2025-12-24 ArXiv 0 11
visibility_off Introduction to Symbolic Regression in the Physical Sciences D. Bartlett, Harry Desmond, Pedro G. Ferreira, G. Kronberger 2025-12-17 ArXiv 0 9
visibility_off Sparse Broad Learning System via Sequential Threshold Least-Squares for Nonlinear System Identification under Noise Zijing Li 2025-11-22 ArXiv 0 0
visibility_off Integrating Score-Based Generative Modeling and Neural ODEs for Accurate Representation of Multiscale Chaotic Dynamics Giulio Del Felice, L. T. Giorgini 2025-11-05 ArXiv 0 8
visibility_off Uncertainties in Physics-informed Inverse Problems: The Hidden Risk in Scientific AI Yoh-ichi Mototake, Makoto Sasaki 2025-11-06 ArXiv 0 8
visibility_off Physics-informed Polynomial Chaos Expansion with Enhanced Constrained Optimization Solver and D-optimal Sampling Qitian Lu, H. Sharma, Michael D. Shields, Luk'avs Nov'ak 2025-12-11 ArXiv 0 4
visibility_off Dyna-Style Reinforcement Learning Modeling and Control of Non-linear Dynamics Karim Abdelsalam, Zeyad Gamal, Ayman El-Badawy 2025-12-24 ArXiv 0 2
visibility_off Learning stochasticity: a nonparametric framework for intrinsic noise estimation G. Pillonetto, A. Giaretta, M. Bisiacco 2025-11-17 ArXiv 0 39
visibility_off Data-Driven Modeling and Correction of Vehicle Dynamics Nguyen Ly, Caroline Tatsuoka, Jai Nagaraj, Jacob Levy, Fernando Palafox, David Fridovich-Keil, Hannah Lu 2025-11-29 ArXiv 0 21
visibility_off Integral Bayesian symbolic regression for optimal discovery of governing equations from scarce and noisy data Oriol Cabanas-Tirapu, Sergio Cobo-López, Savannah E. Sanchez, Forest L. Rohwer, M. Sales-Pardo, R. Guimerà 2025-11-18 ArXiv 0 36
visibility_off Spectrum and Physics-Informed Neural Networks (SaPINNs) for Input-State-Parameter Estimation in Dynamic Systems Subjected to Natural Hazards-Induced Excitation Antonina M. Kosikova, Apostolos F. Psaros, Andrew Smyth 2025-11-10 ArXiv 0 13
visibility_off Data-driven Methods for Delay Differential Equations Dimitri Breda, Xunbi A. Ji, Gábor Orosz, Muhammad Tanveer 2025-12-04 ArXiv 0 4
visibility_off When is a System Discoverable from Data? Discovery Requires Chaos Zakhar Shumaylov, Peter Zaika, Philipp Scholl, Gitta Kutyniok, L. Horesh, C. Schonlieb 2025-11-12 ArXiv 1 55
visibility_off Forecasting Chaotic Dynamics Using a Hybrid System Michele Baia, Franco Bagnoli, T. Matteuzzi 2025-11-20 Complexities 0 2
visibility_off A Tutorial on Dimensionless Learning: Geometric Interpretation and the Effect of Noise Zhengtao Jake Gan, Xiaoyu Xie 2025-12-12 ArXiv 0 0
visibility_off Physics-Informed Neural ODEs with Scale-Aware Residuals for Learning Stiff Biophysical Dynamics Kamalpreet Singh Kainth, Prathamesh Dinesh Joshi, R. Dandekar, R. Dandekar, S. Panat 2025-11-13 ArXiv 0 5
visibility_off SPINI: a structure-preserving neural integrator for hamiltonian dynamics and parametric perturbation Chengtian Liang, Xintong Wen, Zhaoyu Zhu, Lijiong Shen, Yu Wang 2025-12-15 Scientific Reports 0 1
visibility_off KALIKO: Kalman-Implicit Koopman Operator Learning For Prediction of Nonlinear Dynamical Systems Albert H. Li, I. D. Rodriguez, J. W. Burdick, Yisong Yue, A. D. Ames 2025-12-02 ArXiv 0 8
visibility_off Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling Piotr Gwiazda, A. Kazarnikov, A. Marciniak-Czochra, Zuzanna Szyma'nska 2025-12-02 Bulletin of Mathematical Biology 0 35
visibility_off On-line learning of dynamic systems: sparse regression meets Kalman filtering G. Pillonetto, Akram Yazdani, A. Aravkin 2025-11-14 ArXiv 0 59
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index