Symbolic regression

This page was last updated on 2026-08-31 06:37:59 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 5365 80 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 154 26 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 1051 80 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 661 80 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 696 80 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 436 80 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 394 80 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 84 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 59 80 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 104 80 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 392 80 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 74 99 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 186 80 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 An Introduction to Sparse Identification of Nonlinear Dynamics for Engineering Applications Y. Li, A. Larrañaga, Steven L. Brunton, Urban Fasel 2026-07-16 ArXiv 0 10
visibility_off Dynamics-aware identification of governing equations from sparse and noisy data Pongpisit Thanasutives, Yoshinobu Kawahara 2026-07-31 ArXiv 1 11
visibility_off Robust Discovery of Coarse-Grained Continuum Equations from Microscopic Dynamics P. Mondal, Manav Kumar Jalan, Anish Kumar, Shradha Mishra 2026-08-04 ArXiv 0 3
visibility_off Symbolic Neural ODEs: Learning interpretable models from time-series data N. Boddupalli, J. Moehlis 2026-08-22 ArXiv 0 7
visibility_off Hybrid SINDy-EnKF in Learning Chikungunya Dynamics from Incomplete, Noisy or Partially Observed Data B. A. Afful, Changhong Mou, Luis F. Gordillo 2026-07-29 ArXiv 0 7
visibility_off From data chaos to physically interpretable deterministic mapping Dongni Jia, Shuai Li, Xinyi Zuo, Haibo Shi, Junyi Wang, Xiaofeng Zhou 2026-07-13 Nature Communications 0 16
visibility_off Data-driven linear analysis of dynamical systems via nonlinearity-subtracted dynamic mode decomposition Benjamín Herrmann, Katherine Cao, S. Brunton, B. McKeon 2026-08-13 ArXiv 0 80
visibility_off Dynamic mode decomposition with multiple initial conditions for linearizing nonlinear partial differential equations Kanav Singh Rana, Nitu Kumari 2026-08-03 Engineering with Computers 0 19
visibility_off Attractor Geometry Determines the Identifiability Limits of System Discovery Matteo Gallo, Fabio Anselmi, Paolo Lazzari 2026-07-20 ArXiv 2 4
visibility_off Sparse Identification of Systems with Both Abrupt and Slowly Varying Nonlinear Dynamics * Tore Gude, L. Imsland 2026-07-07 2026 European Control Conference (ECC) 0 1
visibility_off Identifying nonlinear dynamical systems using subset regression. Weizhen Li, Qiang Fu, Yifan Hong, Haojian Lu 2026-07-15 Scientific reports 0 16
visibility_off Neural Discovery of Memory and Nonlocal Kernels in Integro-Differential Equations with Constrained Kolmogorov--Arnold Networks Aruzhan Tleubek, Salah A. Faroughi 2026-07-13 ArXiv 0 2
visibility_off Weak form Scientific Machine Learning for Systems Biology: A Tutorial on WENDy N. Heitzman-Breen, Rainey Lyons, Paras Jain, M. Jolly, David M. Bortz 2026-07-03 bioRxiv 0 61
visibility_off Semi-analytical hierarchical Bayesian inference of nonlinear model structure in stochastic dynamics: Applied to compartmental models of infectious diseases B. Robinson, Philippe Bisaillon, R. Sandhu, Mohammad Khalil, J. Edwards, T. Kendzerska, Thomas Walker, Shirley Mills, C. Pettit, D. Poirel, A. Sarkar 2026-07-10 PLOS One 0 30
visibility_off Differential-Embedding Reconstruction of Dynamical Systems from Scalar Time Series A. Shaa, C. Guet 2026-08-17 ArXiv 0 10
visibility_off Genetic Programming-Based Modeling of Systems of Differential Equations N. Haut, Stuart Card, M. Kotanchek 2026-07-13 Proceedings of the Genetic and Evolutionary Computation Conference Companion 0 12
visibility_off Linear and Nonlinear Latent-Space Reduced-Order Models for the Rayleigh--Taylor Instability Téo Granger, B. Nadiga, B. Gréa, A. Briard, Paul Creusy 2026-08-27 ArXiv 0 14
visibility_off Discovering Latent Response Laws in Forced Physical Systems Yi Zhu, Su Chen, Xiaojun Li, Xiuli Du 2026-07-09 ArXiv 0 6
visibility_off On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Baptiste Mathevon, Farah Cherfaoui, Amaury Habrard, M. Sebban 2026-07-26 ArXiv 0 28
visibility_off An interpretable data-driven identification of dynamical systems via universal neural ordinary differential equations Qing-Tong Dong 2026-08-03 Engineering Research Express 0 0
visibility_off Freeze, Then Select: Structured Field Adapters and Stability-Validated Weak Selection for PDE Discovery from Sparse Observations Juncheng Zhong, Chen Shen, Jianfeng Liu, Z. Xiao, Longjiu Luo, Qianrong Wang, Wenjun Xu, Wenlian Lu 2026-07-31 ArXiv 0 5
visibility_off Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Andrea Pomarico, Y. Bao, L. Marš, Salvatore Gao, Tessitore Giorgio Maria, Alberto Giannuzzi, J. Berizzi, Nathan Kutz 2026-07-03 ArXiv 0 14
visibility_off Data-driven reduced modeling of neural dynamics A. Marraffa, R. Krause, V. Mante, G. Haller 2026-07-28 Nature Communications 0 17
visibility_off Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis Isabel Corona Guevara, Yeping Hu 2026-07-31 ArXiv 0 2
visibility_off Koopman-based model predictive control for nonlinear systems with bounded model uncertainty Yangzhe Liu, Hanqiu Bao 2026-08-25 International Journal of Dynamics and Control 0 7
visibility_off A Mathematical Model for Predicting Complex Dynamic Systems Using Hybrid Computational Approaches G. Em Karniadakis, E. Torfs, L. Marchetti 2026-07-28 Global Synthesis in Education Journal 0 18
visibility_off Physics-Guided Spectral Parametric Reduced-Order Modeling for Transient Prediction of Controlled Dynamical Systems Ao Zhang, Tianmin Zhang, A. Cammi, Xiang Wang 2026-07-20 ArXiv 0 38
visibility_off Gaussian process learning with flow map refinement for parameter estimation in dynamical systems Y. Hao, Dongwei Ye 2026-08-23 ArXiv 0 13
visibility_off On a joint simultaneous learning of relevant feature subsets and subspaces in regression-like problems I. Horenko 2026-07-30 ArXiv 0 28
visibility_off Hybrid Analytical Numerical and Machine Learning Frameworks for Solving Deterministic and Stochastic Differential Equations with Stability, Convergence, and Uncertainty Quantification Suresh Kumar Sahani 2026-07-23 Journal of Intelligent Decision Making and Information Science 2 3
visibility_off KOOPMAN-Luenberger Observer Design for Nonlinear Systems with Application to the Monitoring of a Latent Thermal Energy Storage M. Habib, Dario Aguiar, Esther Kieseritzky, T. Barz, Qian Wang 2026-08-11 ArXiv 0 22
visibility_off Physics informed bidirectional LSTM for Bayesian guided grey box modeling of nonlinear dynamical systems L. J, V. T., Gayathri S. Menon 2026-07-14 Engineering Research Express 0 4
visibility_off A novel Data-Driven representation of Linear Systems based on Dynamic Mode Decomposition with Control to deal with noisy data Francesco Giannini 2026-07-01 2026 12th International Conference on Control, Decision and Information Technologies (CoDIT) 0 5
visibility_off RTS Smoother-Guided Learning of Physics-Based Neural Differential Models Ahmet Demirkaya, Georgios Stratis, Tales Imbiriba, Zachary C. Danziger, Deniz Erdoğmuş 2026-07-16 ArXiv 0 18
visibility_off Physics-Integrated Operator Learning via Gaussian Splatting Representations Jihao Zhang, Junyi Guo, Jian-Xun Wang 2026-08-25 ArXiv 0 6
visibility_off Manifold-adapted radial basis functions for reduced-order modelling of chaotic flows Miguel Pérez Cuadrado, Giorgio Maria Cavallazzi, Alfredo Pinelli 2026-07-09 ArXiv 0 2
visibility_off Learning piecewise-smooth dynamical systems D. Murari, Erik Jansson, Chris Budd Obe, C. Schönlieb 2026-08-20 ArXiv 0 52
visibility_off Modelisation of chaotic systems with a latent Stochastic Differential Equation Ismaël Zighed, Nicolas Thome, Patrick Gallinari, T. Sayadi 2026-08-04 ArXiv 0 14
visibility_off Overcoming error-in-variable or stiffness problem in SINDy-like data-driven model discovery L. Fung 2026-07-18 ACM Transactions on AI for Science 0 7
visibility_off Data-driven reconstruction of dynamical systems using Takens'Theorem, manifold learning, and universal function approximators Maximilian Topel, Andrew L. Ferguson 2026-08-05 ArXiv 0 13
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index