Symbolic regression

This page was last updated on 2026-03-23 06:39:10 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 4719 79 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 135 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 939 79 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 609 79 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 635 79 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 409 79 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 330 79 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 53 79 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 101 79 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 322 79 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 62 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 167 79 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 KANDy: Kolmogorov-Arnold Networks and Dynamical System Discovery Kevin Slote, Jeremie Fish, Erik Bollt 2026-02-23 ArXiv 0 5
visibility_off Towards a data-scale independent regulariser for robust sparse identification of non-linear dynamics Jayant Raut, Daniel N. Wilke, Stephan Schmidt 2026-03-05 ArXiv 0 3
visibility_off Ill-Conditioning in Dictionary-Based Dynamic-Equation Learning: A Systems Biology Case Study Yu Feng, Niall M. Mangan, Manu Jayadharan 2026-03-11 ArXiv 0 7
visibility_off PriorIDENT: Prior-Informed PDE Identification from Noisy Data Chengwei Tang, Hao Liu, Dong Wang 2026-03-06 ArXiv 0 5
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 74
visibility_off Differentiable Sparse Identification of Lagrangian Dynamics Zitong Zhang, Hao Sun 2026-03-14 Proceedings of the AAAI Conference on Artificial Intelligence 0 9
visibility_off Discovering Unknown Inverter Governing Equations via Physics-Informed Sparse Machine Learning Jialin Zheng, Ruhaan Batta, Zhong Liu, Xiaonan Lu 2026-02-18 ArXiv 0 1
visibility_off Symbolic Discovery of Stochastic Differential Equations with Genetic Programming Sigur de Vries, Sander W. Keemink, M. Gerven 2026-03-10 ArXiv 0 39
visibility_off KoopGen: Koopman Generator Networks for Representing and Predicting Dynamical Systems with Continuous Spectra Li Su, Jun Shu, Rui Liu, Deyu Meng, Zongben Xu 2026-02-15 ArXiv 0 3
visibility_off Time-Delayed Transformers for Data-Driven Modeling of Low-Dimensional Dynamics A. Alcalde, M. Widhalm, Emre Yılmaz 2026-02-09 ArXiv 0 11
visibility_off Symbolic recovery of PDEs from measurement data Erion Morina, P. Scholl, Martin Holler 2026-02-17 ArXiv 0 5
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 2
visibility_off Dicovering the emergent nonlinear dynamics of acoustically levitated cube clusters Annie Z. Xia, M. Lim, Jason Z. Kim, Bryan VanSaders, Heinrich M. Jaeger 2026-03-16 ArXiv 0 13
visibility_off Uncertainty Quantification in Data-Driven Dynamical Models via Inverse Problem Solving Mohamed Akrout, Dan Wilson 2026-02-23 ArXiv 0 16
visibility_off Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identification from Noisy Data M. Frasch 2026-03-16 ArXiv 0 12
visibility_off Factorized Neural Implicit DMD for Parametric Dynamics Si-Run Chen, Zhecheng Wang, Yixin Chen, Yue Chang, Peter Yichen Chen, E. Grinspun, Jonathan Panuelos 2026-03-11 ArXiv 0 54
visibility_off Trustworthy Koopman Operator Learning: Invariance Diagnostics and Error Bounds Gustav Conradie, Nicolas Boull'e, Jean-Christophe Loiseau, S. Brunton, Matthew J. Colbrook 2026-03-16 ArXiv 0 79
visibility_off An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems Panayiotis Ioannou, P. Liò, P. Cicuta 2026-01-28 ArXiv 0 46
visibility_off Modeling Batch Crystallization under Uncertainty Using Physics-informed Machine Learning Dingqi Nai, Huayu Li, M. Grover, Andrew J Medford 2026-02-06 ArXiv 0 30
visibility_off Physics as the Inductive Bias for Causal Discovery Jianhong Chen, Naichen Shi, Xubo Yue 2026-02-03 ArXiv 0 1
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 Robust Parameter and State Estimation in Multiscale Neuronal Systems Using Physics-Informed Neural Networks Chang Wei, Yangyang Wang, Xueyu Zhu 2026-02-27 ArXiv 0 4
visibility_off Topological Entropy Correlates with the Predictive Power of Multiplexed Ensemble Reservoir Computing Suvankar Halder, Christopher M. Kim, V. Periwal 2026-02-07 bioRxiv 0 31
visibility_off Dynamics-Informed Deep Learning for Predicting Extreme Events E. Katsidoniotaki, T. Sapsis 2026-03-11 ArXiv 0 41
visibility_off Scalable Pseudospectral Analysis via Low-Rank Approximations of Dynamical Systems V. Kostić, D. Cvetković, L. Cvetković 2026-02-02 ArXiv 0 18
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 Encoding Cumulation to Learn Perturbative Nonlinear Oscillatory Dynamics. Teng Ma, Tingyi Gao, Wei Cui, A. Frangi, Gang Yan, Lin Zhao 2026-03-06 Advanced science 0 13
visibility_off Latent-Variable Learning of SPDEs via Wiener Chaos Sebastian Zeng, A. Petersson, Wolf-gang Bock 2026-02-12 ArXiv 1 3
visibility_off Latent Autoencoder Ensemble Kalman Filter for Data assimilation Xin T. Tong, Yanyan Wang, Liang Yan 2026-03-06 ArXiv 0 2
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 From Basins to safe sets: a machine learning perspective on chaotic dynamics David Valle, Alexandre Wagemakers, M. Sanju'an 2026-01-29 ArXiv 0 3
visibility_off Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows Xiao Xue, Tianyue Yang, Mingyang Gao, Leyu Pan, Maida Wang, Kewei Zhu, Shuo Wang, Jiuling Li, M. T. Eikelder, Peter V. Coveney 2026-02-17 ArXiv 0 7
visibility_off A Score Filter Enhanced Data Assimilation Framework for Data-Driven Dynamical Systems Jingqiao Tang, Ryan Bausback, Feng Bao, Guannan Zhang, P. Huynh 2026-03-16 ArXiv 0 3
visibility_off A sliding-window approach for latent restoring force modeling M. Floren, Jan Swevers 2026-02-25 ArXiv 1 3
visibility_off Controlled oscillation modeling using port-Hamiltonian neural networks M. Linares, Guillaume Doras, Thomas H'elie 2026-02-17 ArXiv 0 7
visibility_off Identification of Port-Hamiltonian Differential-Algebraic Equations from Input-Output Data N. Hagelaars, G. V. Otterdijk, S. Moradi, Roland Tóth, N. Jaensson, M. Schoukens 2026-01-23 ArXiv 0 17
visibility_off Foundation Inference Models for Ordinary Differential Equations Maximilian Mauel, Johannes R. Hubers, D. Berghaus, Patrick Seifner, Ramsés J. Sánchez 2026-02-09 ArXiv 1 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 5
visibility_off Divergence-Free Diffusion Models for Incompressible Fluid Flows Wilfried Genuist, 'Eric Savin, F. Gatti, Didier Clouteau 2026-01-27 ArXiv 1 13
visibility_off Learning Data-Efficient and Generalizable Neural Operators via Fundamental Physics Knowledge Siying Ma, M. M. Zadeh, Mauricio Soroco, Wuyang Chen, Jiguo Cao, V. Ganesh 2026-02-16 ArXiv 1 27
visibility_off On the Role of Consistency Between Physics and Data in Physics-Informed Neural Networks Nicol'as Becerra-Zuniga, Lucas Lacasa, Eusebio Valero, Gonzalo Rubio 2026-02-11 ArXiv 0 2
visibility_off Machine Learning for Complex Systems Dynamics: Detecting Bifurcations in Dynamical Systems with Deep Neural Networks Swadesh Pal, R. Melnik 2026-02-14 ArXiv 0 5
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index