Symbolic regression

This page was last updated on 2026-03-30 06:48:30 UTC

Click here for a quick intro of the page! help

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	4749	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	945	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	611	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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences	638	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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences	332	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	80	27	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	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	Data-driven discovery of partial differential equations	S. Rudy, S. Brunton, J. Proctor, J. Kutz	2016-09-21	Science Advances	1610	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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences	326	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	169	79	open_in_new
Abstract	Title	Authors	Publication Date	Journal/ Conference	Citation count	Highest h-index	View recommendations

Recommended articles on Symbolic regression

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	From Data to Laws: Neural Discovery of Conservation Laws Without False Positives	Rahul Ray	2026-03-20	ArXiv	0	2
visibility_off	Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization	Grant Norman, Conor Rowan, K. Maute, Alireza Doostan	2026-02-13	ArXiv	0	55
visibility_off	Differentiable Sparse Identification of Lagrangian Dynamics	Zitong Zhang, Hao Sun	2026-03-14	DBLP	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	An information-based model selection criterion for data-driven model discovery	Michael C. Chung, Alen Zacharia, Juan Guan	2026-02-24	ArXiv	0	3
visibility_off	Symbolic Graph Networks for Robust PDE Discovery from Noisy Sparse Data	Xingyu Chen, Junxiu An, Junjian Guo, Yuqian Zhou	2026-03-23	ArXiv	0	3
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	Sparse Weak-Form Discovery of Stochastic Generators	A. EshwarR, G. Honnavar	2026-03-21	ArXiv	0	7
visibility_off	In-Context System Identification for Nonlinear Dynamics Using Large Language Models	Linyu Lin	2026-02-07	ArXiv	0	10
visibility_off	Weak-PDE-Net: Discovering Open-Form PDEs via Differentiable Symbolic Networks and Weak Formulation	Xinxin Li, Xin Cui, Jingyang Qi, Juan Zhang, Da Li, Junping Yin	2026-03-24	ArXiv	0	1
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	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	Turning Time Series into Algebraic Equations: Symbolic Machine Learning for Interpretable Modeling of Chaotic Time Series	Madhurima Panja, Grace Younes, Tanujit Chakraborty	2026-03-07	ArXiv	0	6
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	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	Multivariate Identification via Linear Projection of Eigenvectors	Dong-Hwan Kim	2026-03-06	Mathematics	0	2
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	From synthetic turbulence to true solutions: A deep diffusion model for discovering periodic orbits in the Navier-Stokes equations	Jeremy P Parker, Tobias M. Schneider	2026-02-26	ArXiv	0	3
visibility_off	LawMind: A Law-Driven Paradigm for Discovering Analytical Solutions to Partial Differential Equations	Min-Yi Zheng, Shengqi Zhang, Liancheng Wu, Jinghui Zhong, Shiyi Chen, Y. Ong	2026-03-15	ArXiv	0	7
visibility_off	GasNiTROM: Model Reduction via Non-Intrusive Optimization of Oblique Projection Operators and Guaranteed-Stable Latent-Space Dynamics	Cole J. Errico, Alberto Padovan, Daniel J. Bodony	2026-03-22	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	Neuro-Symbolic Multitasking: A Unified Framework for Discovering Generalizable Solutions to PDE Families	Yipeng Huang, Dejun Xu, Zexin Lin, Zhenzhong Wang, Min Jiang	2026-02-12	ArXiv	0	10
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	Unlearning Noise in PINNs: A Selective Pruning Framework for PDE Inverse Problems	Yong-Sheng Chen, Yong Chen, Wei Guo, Xinghui Zhong	2026-02-23	ArXiv	0	14
visibility_off	Hierarchical Inference and Closure Learning via Adaptive Surrogates for ODEs and PDEs	Pengyun Zhang, A. Vadeboncoeur, Alex Glyn-Davies, Mark Girolami	2026-03-04	ArXiv	0	4
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	Auto-differentiable data assimilation: Co-learning of states, dynamics, and filtering algorithms	Melissa Adrian, D. Sanz-Alonso, Rebecca Willett	2026-03-21	ArXiv	0	2
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	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	Inverse Neural Operator for ODE Parameter Optimization	Zhi-Song Liu, W. Peng, Helmi Toropainen, Ammar Kheder, Andreas Rupp, H. Froning, Xiaojie Lin, Michael Boy	2026-03-12	ArXiv	0	6
visibility_off	KAN-Based Parameter Estimation of the FitzHugh–Nagumo Model Under Noisy Conditions	Yitao Fang, Han Zhang, N. Gunasekaran	2026-02-01	IEEE Transactions on Consumer Electronics	0	24
visibility_off	LEVDA: Latent Ensemble Variational Data Assimilation via Differentiable Dynamics	Phillip Si, Peng Chen	2026-02-23	ArXiv	1	2
visibility_off	Variational Garrote for Sparse Inverse Problems	K. Lee, H. Soh, Junghyo Jo	2026-03-13	ArXiv	0	1
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	Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach	Gianluca Fabiani, M. Kavousanakis, Constantinos I. Siettos, Ioannis G. Kevrekidis	2026-03-23	ArXiv	0	16
Abstract	Title	Authors	Publication Date	Journal/Conference	Citation count	Highest h-index