Symbolic regression

This page was last updated on 2026-02-02 06:32:50 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 4547 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 891 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 593 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 614 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 400 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 318 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 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 303 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 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 2
visibility_off Information theory and discriminative sampling for model discovery Yuxuan Bao, J. N. Kutz 2025-12-17 ArXiv 1 3
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 Data-driven Interpretable Hybrid Robot Dynamics Christopher E. Mower, Rui Zong, Haitham Bou-Ammar 2025-12-10 ArXiv 0 29
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 1
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 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 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 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 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 0
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 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 Robust Physics Discovery from Highly Corrupted Data: A PINN Framework Applied to the Nonlinear Schr\"odinger 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 Differentiation methods as a systematic uncertainty source in equation discovery Maria Khilchuk, Ilya Markov, Alexander Hvatov 2025-12-14 ArXiv 0 2
visibility_off An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems Panayiotis Ioannou, Pietro Lio, Pietro Cicuta 2026-01-28 ArXiv 0 0
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 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 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 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 Phase-IDENT: Identification of Two-phase PDEs with Uncertainty Quantification Edward L. Yang, Roy Y. He 2026-01-17 ArXiv 0 0
visibility_off Reduced-order complex network modeling of parametric fluid dynamic systems under partial observability Zihao Wang, Guiyong Zhang, Tiezhi Sun, Zhe Sun, Zhifan Zhang, Bo Zhou 2026-01-26 Nonlinear Dynamics 0 11
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 1 20
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 The Vekua Layer: Exact Physical Priors for Implicit Neural Representations via Generalized Analytic Functions Vladimer Khasia 2025-12-11 ArXiv 0 1
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 Iterative Residual Dynamic Mode Decomposition for Prediction and Control of Dynamical Systems Youngkyoung Kong, Inkyu Jang, H. J. Kim 2025-12-09 2025 IEEE 64th Conference on Decision and Control (CDC) 0 11
visibility_off Forecasting N-Body Dynamics: A Comparative Study of Neural Ordinary Differential Equations and Universal Differential Equations S. SuriyaR, Prathamesh Dinesh Joshi, R. Dandekar, R. Dandekar, S. Panat 2025-12-12 ArXiv 0 5
visibility_off Data-driven functional state estimation of complex networks Yuan Zhang, Ziyuan Luo, Wenxuan Xu, Jiayu Wu, Wenqi Cao, Ranbo Cheng, Tingting Qin, Yuanqing Xia, Mohamed Darouach, Aming Li, T. Fernando 2025-12-07 ArXiv 0 4
visibility_off Spectral Embedding via Chebyshev Bases for Robust DeepONet Approximation Muhammad Abid, Omer San 2025-12-09 ArXiv 0 1
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 9
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index