Symbolic regression

This page was last updated on 2025-06-23 11:23:08 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 3888 70 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 107 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 750 70 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 526 70 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 523 70 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 358 70 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 268 70 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 71 20 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 46 70 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 84 70 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 228 70 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 46 95 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 139 70 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 Robust Moment Identification for Nonlinear PDEs via a Neural ODE Approach Shaoxuan Chen, Su Yang, Panayotis Kevrekidis, Wei Zhu 2025-06-05 ArXiv 0 1
visibility_off Optimizing Hard Thresholding for Sparse Model Discovery Derek W. Jollie, S. McCalla 2025-04-28 ArXiv 0 9
visibility_off Mesh-free sparse identification of nonlinear dynamics Mars Liyao Gao, J. N. Kutz, Bernat Font 2025-05-21 ArXiv 0 1
visibility_off IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Roy Y. He, Hao Liu, Wenjing Liao, Sung Ha Kang 2025-06-09 ArXiv 0 1
visibility_off A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model Jinchao Feng, Sui Tang 2025-05-11 ArXiv 0 2
visibility_off Data-driven discovery of the equations of turbulent convection C. Wareing, Alasdair T. Roy, Matthew Golden, R. Grigoriev, Steven M. Tobias 2025-05-15 ArXiv 0 24
visibility_off Transforming physics-informed machine learning to convex optimization Letian Yi, Siyuan Yang, Ying Cui, Zhilu Lai 2025-05-02 ArXiv 0 0
visibility_off Neuro-Symbolic Operator for Interpretable and Generalizable Characterization of Complex Piezoelectric Systems Abhishek Chandra, Taniya Kapoor, M. Curti, K. Tiels, E. Lomonova 2025-05-30 ArXiv 0 25
visibility_off Identifiability Challenges in Sparse Linear Ordinary Differential Equations Cecilia Casolo, Soren Becker, Niki Kilbertus 2025-06-11 ArXiv 0 13
visibility_off Adaptive Physics-Informed System Modeling with Control for Nonlinear Structural System Estimation Biqi Chen, Chenyu Zhang, Jun Zhang, Ying Wang 2025-05-10 ArXiv 0 0
visibility_off Physics-informed Reduced Order Modeling of Time-dependent PDEs via Differentiable Solvers Nima Hosseini Dashtbayaz, H. Salehipour, Adrian Butscher, Nigel Morris 2025-05-20 ArXiv 0 17
visibility_off On the emergence of numerical instabilities in Next Generation Reservoir Computing Edmilson Roque dos Santos, Erik M. Bollt 2025-05-01 ArXiv 0 1
visibility_off Globalizing manifold-based reduced models for equations and data B'alint Kasz'as, George Haller 2025-05-09 ArXiv 0 0
visibility_off Identification of Differential Equations by Dynamics-Guided Weighted Weak Form with Voting Jiahui Cheng, Sung Ha Kang, Haomin Zhou, Wenjing Liao 2025-06-04 ArXiv 0 2
visibility_off SINDybrid: automatic generation of hybrid models for dynamic systems Ulderico Di Caprio, M. Leblebici 2025-06-14 ArXiv 0 14
visibility_off Data-driven discovery of nonlinear dynamics in complex systems through phase-space informed neural ordinary differential equations David Garrido González, N. Saura, S. Benkadda, P. Beyer 2025-06-01 Physics of Plasmas 0 29
visibility_off Data-assimilated model-informed reinforcement learning D. E. Ozan, Andrea N'ovoa, Georgios Rigas, Luca Magri 2025-06-02 ArXiv 0 2
visibility_off A CFL-type Condition and Theoretical Insights for Discrete-Time Sparse Full-Order Model Inference L. Gkimisis, Süleyman Yıldız, Peter Benner, Thomas Richter 2025-05-02 ArXiv 0 5
visibility_off Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing Declan A. Norton, Yuanzhao Zhang, M. Girvan 2025-06-05 ArXiv 0 20
visibility_off A Unified Framework for Simultaneous Parameter and Function Discovery in Differential Equations Shalev Manor, Mohammad Kohandel 2025-05-22 ArXiv 0 0
visibility_off Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces Alejandro N Diaz, Shane A. McQuarrie, John T. Tencer, P. Blonigan 2025-06-11 ArXiv 0 14
visibility_off Physics-Informed Neural Network-Based Discovery of Hyperelastic Constitutive Models from Extremely Scarce Data Hyeonbin Moon, Dong-Oh Park, Hanbin Cho, Hong-Kyun Noh, Jae Hyuk Lim, S. Ryu 2025-04-28 ArXiv 1 8
visibility_off Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares Aurora Poggi, Giuseppe Alessio D’Inverno, Hjalmar Brismar, Ozan Oktem, Matthieu Barreau, Kateryna Morozovska 2025-05-23 ArXiv 0 9
visibility_off Enabling Local Neural Operators to perform Equation-Free System-Level Analysis Gianluca Fabiani, H. Vandecasteele, Somdatta Goswami, Constantinos Siettos, Ioannis G. Kevrekidis 2025-05-05 ArXiv 1 8
visibility_off System Identification Using Kolmogorov-Arnold Networks: A Case Study on Buck Converters Nart Gashi, Panagiotis Kakosimos, George Papafotiou 2025-06-12 ArXiv 0 9
visibility_off Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison Jan C. Schulze, Alexander Mitsos 2025-06-15 ArXiv 0 4
visibility_off A Hybrid Framework for Efficient Koopman Operator Learning Alexander Estornell, Leonard Jung, Alenna Spiro, Mario Sznaier, Michael Everett 2025-04-25 ArXiv 0 1
visibility_off Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems Xiaolong He, Yeonjong Shin, Anthony Gruber, Sohyeon Jung, Kookjin Lee, Youngsoo Choi 2025-06-10 ArXiv 0 3
visibility_off Data-Driven Decomposition of Conservative and Non-Conservative Dynamics in Multiscale Systems L. T. Giorgini 2025-05-03 ArXiv 0 6
visibility_off Velocity-Inferred Hamiltonian Neural Networks: Learning Energy-Conserving Dynamics from Position-Only Data Ruichen Xu, Zongyu Wu, Luoyao Chen, Georgios Kementzidis, Siyao Wang, Haochun Wang, Yiwei Shi, Yuefan Deng 2025-05-05 ArXiv 0 1
visibility_off Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics Martine Dyring Hansen, Elena Celledoni, Benjamin Kwanen Tampley 2025-05-26 ArXiv 0 0
visibility_off Deep Koopman operator framework for causal discovery in nonlinear dynamical systems Juan Nathaniel, Carla Roesch, Jatan Buch, Derek DeSantis, Adam Rupe, Kara Lamb, Pierre Gentine 2025-05-20 ArXiv 1 7
visibility_off Machine learning and partial differential equations: benchmark, simplify, and discover P. Koumoutsakos 2025-06-18 Data-Centric Engineering 0 2
visibility_off Identification of hybrid dynamic systems via a sparse regression algorithm Nico Novelli, P. Belardinelli, S. Lenci 2025-05-12 Nonlinear Dynamics 0 13
visibility_off Interpretability and Generalization Bounds for Learning Spatial Physics A. Queiruga, Theo Gutman-Solo, Shuai Jiang 2025-06-18 ArXiv 0 13
visibility_off Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs S. S. Menon, Ameya D. Jagtap 2025-05-06 ArXiv 0 2
visibility_off Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints Avik Pal, Alan Edelman, Christopher Rackauckas 2025-05-26 ArXiv 1 7
visibility_off A general physics-constrained method for the modelling of equation's closure terms with sparse data Tian-jie Chen, Shengping Liu, Li Liu, Heng Yong 2025-04-30 ArXiv 0 1
visibility_off Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming Linus Langenkamp, Philip Hannebohm, Bernhard Bachmann 2025-05-06 ArXiv 0 1
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index