Symbolic regression

This page was last updated on 2026-01-26 06:15:42 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 4510 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 128 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 886 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 590 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 611 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 399 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 317 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 51 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 98 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 301 77 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 59 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 Sparse Identification of Nonlinear Distributed-Delay Dynamics via the Linear Chain Trick Mohammed Alanazi, Majid Bani-Yaghoub 2026-01-20 ArXiv 0 1
visibility_off Sindy on attracting manifolds Diemen Delgado-Cano, Erick Kracht, Urban Fasel, Benjamin Herrmann 2025-12-04 Nonlinear Dynamics 0 13
visibility_off Information theory and discriminative sampling for model discovery Yuxuan Bao, J. N. Kutz 2025-12-17 ArXiv 0 3
visibility_off Data assimilation and discrepancy modeling with shallow recurrent decoders Yuxuan Bao, J. N. Kutz 2025-12-01 ArXiv 1 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 Symmetry inspired learning of governing equations from noisy data Haoran Chen, Dunhui Xiao 2026-01-01 Physics of Fluids 0 4
visibility_off An adjoint method for training data-driven reduced-order models Donglin Liu, Francisco Garc'ia Atienza, Mengwu Guo 2026-01-12 ArXiv 0 0
visibility_off Inverse problems for history-enriched linear model reduction Arjun Vijaywargiya, G. Biros 2026-01-11 ArXiv 0 51
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, Frank Allgöwer 2025-12-06 ArXiv 0 11
visibility_off Learning Coupled System Dynamics under Incomplete Physical Constraints and Missing Data Esha Saha, Hao Wang 2025-12-28 ArXiv 0 1
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 Data-driven stochastic reduced-order modeling of parametrized dynamical systems Andrew F. Ilersich, Kevin Course, Prasanth B. Nair 2026-01-15 ArXiv 0 3
visibility_off Learning structured population models from data with WSINDy Rainey Lyons, Vanja Dukic, David M. Bortz 2025-12-01 PLOS Computational Biology 0 3
visibility_off A Machine Learning Framework for Predicting Solutions to Nonlinear Differential Equations Vinayak kishan, Nirmale Lecturer, A.K.Bhuvaneswari, Kalpana Devarajan, S.Meher Taj, C.Ruby, G.Nandini 2025-12-12 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG) 0 0
visibility_off GIMLET: Generalizable and Interpretable Model Learning through Embedded Thermodynamics Suguru Shiratori, Elham Kiyani, K. Shukla, G. Karniadakis 2025-12-22 ArXiv 0 19
visibility_off Noise Reduction in Chaotic Systems for Improved HAVOK Linear Reconstructions Abdullah Bin Queyam, Ramesh Kumar, M. Tripathy 2025-12-05 2025 5th IEEE International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC) 0 19
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 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 1 1
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 ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees Andrea Goertzen, Sunbochen Tang, Navid Azizan 2025-12-01 ArXiv 0 16
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 SPIKE: Sparse Koopman Regularization for Physics-Informed Neural Networks J. M. Minoza 2026-01-15 ArXiv 0 4
visibility_off Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference Shane A. Mcquarrie, Mengwu Guo, Anirban Chaudhuri 2025-12-30 ArXiv 0 6
visibility_off Introduction to Symbolic Regression in the Physical Sciences D. Bartlett, Harry Desmond, Pedro G. Ferreira, G. Kronberger 2025-12-17 ArXiv 1 9
visibility_off Learning Stiff Dynamical Operators: Scaling, Fast-Slow Excitation, and Eigen-Consistent Neural Models Mauro Valorani 2026-01-04 ArXiv 0 0
visibility_off Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems Tomoki Koike, Prakash Mohan, M. H. D. Frahan, Julie Bessac, Elizabeth Qian 2026-01-17 ArXiv 0 9
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 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 Deep Robust Koopman Learning from Noisy Data Aditya Singh, Rajpal Singh, J. Keshavan 2026-01-05 ArXiv 0 9
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 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 SPINI: a structure-preserving neural integrator for hamiltonian dynamics and parametric perturbation Chengtian Liang, Xintong Wen, Zhaoyu Zhu, Lijiong Shen, Yu Wang 2025-12-01 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 High-Fidelity Modeling of Stochastic Chemical Dynamics on Complex Manifolds: A Multi-Scale SIREN-PINN Framework for the Curvature-Perturbed Ginzburg-Landau Equation Julian Evan Chrisnanto, Salsabila Rahma Alia, Nurfauzi Fadillah, Y. H. Chrisnanto 2026-01-13 ArXiv 0 3
visibility_off Parametric Probabilistic Manifold Decomposition for Nonlinear Model Reduction Jiaming Guo, Dunhui Xiao 2026-01-12 ArXiv 0 1
visibility_off Identifying Differential Equations in Fourier Domain (FourierIdent) Mengyi Tang, Hao Liu, Wenjing Liao, Sung Ha Kang 2026-01-17 Journal of Scientific Computing 0 4
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 36
visibility_off A universal linearized subspace refinement framework for neural networks Wenbo Cao, Weiwei Zhang 2026-01-20 ArXiv 0 6
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index