Symbolic regression

This page was last updated on 2026-02-16 06:33:43 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 4593 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 906 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 598 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 620 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 403 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 320 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 79 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 52 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 99 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 304 77 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 59 98 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 162 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 2
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 Knowledge-Informed Kernel State Reconstruction for Interpretable Dynamical System Discovery Luca Muscarnera, Silas Ruhrberg Est'evez, Samuel Holt, Evgeny S. Saveliev, M. Schaar 2026-01-29 ArXiv 0 73
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 Learning Coupled System Dynamics under Incomplete Physical Constraints and Missing Data Esha Saha, Hao Wang 2025-12-28 ArXiv 0 2
visibility_off Sparse identification of delay equations with distributed memory Dimitri Breda, Muhammad Tanveer, Jianhong Wu 2025-12-24 ArXiv 1 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 Time-Delayed Transformers for Data-Driven Modeling of Low-Dimensional Dynamics Albert Alcalde, Markus Widhalm, Emre Yilmaz 2026-02-09 ArXiv 0 0
visibility_off Residual dynamic mode decomposition with control for nonlinear dynamic systems Jacob Rains, Daning Huang, Yi Wang 2026-01-16 Structural and Multidisciplinary Optimization 0 6
visibility_off NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations Maedeh Makki, Satish Chandran, Maziar Raissi, Adrien Grenier, Behzad Mohebbi 2026-01-23 ArXiv 0 3
visibility_off GIMLET: Generalizable and Interpretable Model Learning through Embedded Thermodynamics Suguru Shiratori, Elham Kiyani, K. Shukla, G. Karniadakis 2025-12-22 ArXiv 0 20
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 Physics-guided curriculum learning for the identification of reaction-diffusion dynamics from partial observations Hanyu Zhou, Yuansheng Cao, Yaomin Zhao 2026-01-24 ArXiv 0 1
visibility_off On the Effectiveness of Sparse Identification Methods to Detect Nonlinear Models of Oscillatory Dynamics in Psychology and the Life Sciences. A. Selvitella, Elliot Allen 2026-01-01 Nonlinear dynamics, psychology, and life sciences 0 1
visibility_off Robust Physics Discovery from Highly Corrupted Data: A PINN Framework Applied to the Nonlinear Schrödinger Equation Pietro de Oliveira Esteves 2026-01-07 ArXiv 0 0
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 An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems Panayiotis Ioannou, P. Liò, Pietro Cicuta 2026-01-28 ArXiv 0 8
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 Modeling Batch Crystallization under Uncertainty Using Physics-informed Machine Learning Dingqi Nai, Huayu Li, Martha Grover, Andrew Medford 2026-02-06 ArXiv 0 3
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 Physics as the Inductive Bias for Causal Discovery Jianhong Chen, Naichen Shi, Xubo Yue 2026-02-03 ArXiv 0 1
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 Turning mechanistic models into forecasters by using machine learning Amit K. Chakraborty, Hao Wang, Pouria Ramazi 2026-02-04 ArXiv 0 15
visibility_off Out-of-Distribution Generalization for Neural Physics Solvers Zhao Wei, Chin Chun Ooi, Jian Cheng Wong, Abhishek Gupta, P. Chiu, Y. Ong 2026-01-27 ArXiv 0 33
visibility_off Deep Robust Koopman Learning from Noisy Data Aditya Singh, Rajpal Singh, J. Keshavan 2026-01-05 ArXiv 0 9
visibility_off Differentiable Modeling for Low-Inertia Grids: Benchmarking PINNs, NODEs, and DP for Identification and Control of SMIB System Shinhoo Kang, Sangwook Kim, Sehyun Yun 2026-02-10 ArXiv 0 0
visibility_off Toward Adaptive Non-Intrusive Reduced-Order Models: Design and Challenges Amirpasha Hedayat, Alberto Padovan, Karthik Duraisamy 2026-02-11 ArXiv 0 6
visibility_off Physics-informed machine learning for reconstruction of dynamical systems with invariant measure score matching Yongsheng Chen, Suddhasattwa Das, Wei Guo, Xinghui Zhong 2026-01-19 ArXiv 0 2
visibility_off Minimal realization time-delay Koopman analysis for stochastic dynamical system identification Biqi Chen, Ying Wang 2026-02-04 Advances in Structural Engineering 0 5
visibility_off Latent-Variable Learning of SPDEs via Wiener Chaos Sebastian Zeng, Andreas Petersson, Wolf-gang Bock 2026-02-12 ArXiv 0 0
visibility_off Reduced-order complex network modeling of parametric fluid dynamic systems under partial observability Zihao Wang, Guiyong Zhang, T. Sun, Zhe Sun, Zhifan Zhang, Bo Zhou 2026-01-26 Nonlinear Dynamics 0 25
visibility_off PI-MFM: Physics-informed multimodal foundation model for solving partial differential equations Min Zhu, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer, Lu Lu 2025-12-28 ArXiv 3 20
visibility_off Efficient Dynamics: Reduced‐Order Modeling of the Time‐Dependent Schrödinger Equation K. Owolabi 2025-12-30 Advanced Physics Research 0 41
visibility_off Duffing system parameter estimation by inverse physics-informed neural networks with sine activation function Maciej Czarnacki 2026-02-01 Advances in Science and Technology Research Journal 0 0
visibility_off Controlling synchronization dynamics via physics-informed neural networks Kaiming Luo 2026-01-01 ArXiv 0 0
visibility_off Reduced Order Modeling for Tsunami Forecasting with Bayesian Hierarchical Pooling Shane X. Coffing, John Tipton, Arvind T. Mohan, Darren Engwirda 2025-12-22 ArXiv 0 2
visibility_off Identification of Port-Hamiltonian Differential-Algebraic Equations from Input-Output Data N.Hagelaars, G. V. Otterdijk, S. Moradi, R. T'oth, N. Jaensson, M. Schoukens 2026-01-23 ArXiv 0 10
visibility_off MAD-NG: Meta-Auto-Decoder Neural Galerkin Method for Solving Parametric Partial Differential Equations Qiuqi Li, Yiting Liu, Jin Zhao, Wencan Zhu 2025-12-25 ArXiv 1 1
visibility_off An Inverse Scattering Inspired Fourier Neural Operator for Time-Dependent PDE Learning Rixin Yu 2025-12-22 ArXiv 0 2
visibility_off Foundation Inference Models for Ordinary Differential Equations Maximilian Mauel, Johannes R. Hubers, David Berghaus, Patrick Seifner, Ramsés J. Sánchez 2026-02-09 ArXiv 0 5
visibility_off PHDME: Physics-Informed Diffusion Models without Explicit Governing Equations Kaiyuan Tan, Kendra Givens, Peilun Li, Thomas Beckers 2026-01-29 ArXiv 0 3
visibility_off Optimal Control-Based Falsification of Learnt Dynamics via Neural ODEs and Symbolic Regression Lasse Kotz, Jonas Sjoberg, Knut AAkesson 2026-01-18 ArXiv 0 3
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index