Symbolic regression

This page was last updated on 2025-10-13 06:12:44 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 4191 73 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 120 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 817 73 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 556 73 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 560 73 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 374 73 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 297 73 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 23 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 73 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 91 73 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 268 73 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 53 96 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 150 73 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, M. Naraghi-Pour 2025-09-11 ArXiv 0 20
visibility_off Implicit Runge-Kutta based sparse identification of governing equations in biologically motivated systems Mehrdad Anvari, H. Marasi, Hossein Kheiri 2025-09-02 Scientific Reports 0 4
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 32
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 Data-Driven Discovery of Multi-Dimensional Breakage Population Balance Equations Suet Lin Leong, Firnaaz Ahamed, Yong Kuen Ho 2025-08-19 ArXiv 0 6
visibility_off Data driven feedback linearization of nonlinear control systems via Lie derivatives and stacked regression approach Lakshmi Priya, Andreas Schwung 2025-08-18 ArXiv 0 2
visibility_off Realizing Reduced and Sparse Biochemical Reaction Networks from Dynamics M. Filo, M. Khammash 2025-08-25 ArXiv 0 8
visibility_off Hyperparameter Optimization in the Estimation of PDE and Delay-PDE models from data Oliver Mai, Tim W. Kroll, Uwe Thiele, Oliver Kamps 2025-08-18 ArXiv 0 1
visibility_off DKFNet: Differentiable Kalman Filter for Field Inversion and Machine Learning Yuan Wu, Sicheng He 2025-09-09 ArXiv 0 0
visibility_off Discovering equations from data: symbolic regression in dynamical systems Beatriz R. Brum, L. Lober, I. Previdelli, Francisco A. Rodrigues 2025-08-27 ArXiv 0 14
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 Universal Learning of Nonlinear Dynamics Evan Dogariu, Anand Brahmbhatt, Elad Hazan 2025-08-16 ArXiv 0 62
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 Approximating the universal thermal climate index using sparse regression with orthogonal polynomials Sabin Roman, Gregor Skok, L. Todorovski, S. Džeroski 2025-08-15 ArXiv 0 65
visibility_off Next-Generation Reservoir Computing for Dynamical Inference Rok Cestnik, E. A. Martens 2025-09-14 ArXiv 0 7
visibility_off FNODE: Flow-Matching for data-driven simulation of constrained multibody systems Hongyu Wang, Jingquan Wang, D. Negrut 2025-08-29 ArXiv 0 30
visibility_off Noise estimation of SDE from a single data trajectory Munawar Ali, Purba Das, Qi Feng, L. Gao, Guang Lin 2025-09-29 ArXiv 0 1
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 Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements Xuyang Li, Mahdi Masmoudi, Rami Gharbi, Nizar Lajnef, Vishnu Naresh Boddeti 2025-08-29 ArXiv 0 31
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 Stoch-IDENT: New Method and Mathematical Analysis for Identifying SPDEs from Data Jianbo Cui, Roy Y. He 2025-08-26 ArXiv 0 0
visibility_off Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks Zongyu Wu, Ruichen Xu, Luoyao Chen, Georgios Kementzidis, Siyao Wang, Yuefan Deng 2025-08-26 ArXiv 0 2
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 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 Nested Operator Inference for Adaptive Data-Driven Learning of Reduced-order Models Nicole Aretz, Karen Willcox 2025-08-15 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 Current state and open problems in universal differential equations for systems biology Maren Philipps, Nina Schmid, Jan Hasenauer 2025-08-30 NPJ Systems Biology and Applications 0 3
visibility_off Sequential estimation of disturbed aerodynamic flows from sparse measurements via a reduced latent space Hanieh Mousavi, Anya Jones, Jeff Eldredge 2025-09-04 ArXiv 0 1
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 1
visibility_off Weak Form Learning for Mean-Field Partial Differential Equations: an Application to Insect Movement Seth Minor, B. Elderd, Benjamin Van Allen, David M. Bortz, Vanja Dukic 2025-10-09 ArXiv 0 22
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 2
visibility_off Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification Sanket R. Jantre, Deepak Akhare, Zhiyuan Wang, Xiaoning Qian, Nathan M. Urban 2025-08-26 ArXiv 0 6
visibility_off Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems Aleksandra Jekic, Afroditi Natsaridou, S. Riemer-Sørensen, Helge Langseth, Odd Erik Gundersen 2025-09-24 ArXiv 0 22
visibility_off Learning Spatio-Temporal Dynamics via Operator-Valued RKHS and Kernel Koopman Methods Mahishanka Withanachchi 2025-08-23 ArXiv 0 0
visibility_off Probabilistic and nonlinear compressive sensing Lukas Silvester Barth, Paulo von Petersenn 2025-09-18 ArXiv 0 1
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 Uncertainty Propagation Networks for Neural Ordinary Differential Equations Hadi Jahanshahi, Zheng H. Zhu 2025-08-22 ArXiv 0 2
visibility_off Convolutional autoencoder-augmented sparse identification of noisy nonlinear fluid dynamics from unlabelled data Meng-Tao Zhang, Fanfan Zeng, M. Yousif, Zizhao Zhu, Jung Sub Lee, Heechang Lim 2025-09-01 Physics of Fluids 0 10
visibility_off Reduced-order modeling of Hamiltonian dynamics based on symplectic neural networks Yongsheng Chen, Wei Guo, Qi Tang, Xinghui Zhong 2025-08-16 ArXiv 0 2
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 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 2
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index