Symbolic regression

This page was last updated on 2026-10-19 06:39:41 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. L. 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 5639 81 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 161 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 1100 81 open_in_new
visibility_off Chaos as an intermittently forced linear system S. Brunton, Bingni W. Brunton, J. L. Proctor, E. Kaiser, J. Kutz 2016-08-18 Nature Communications 682 81 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 709 81 open_in_new
visibility_off Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics , Steve Brunton, J. L. Proctor, J. Kutz 2016-05-26 IEEE Transactions on Molecular, Biological and Multi-Scale Communications, IEEE Transactions on Molecular Biological and Multi-Scale Communications 443 81 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 414 81 open_in_new
visibility_off Multidimensional Approximation of Nonlinear Dynamical Systems Patrick Gelß, Stefan Klus, J. Eisert, C. Schütte 2018-09-07 Journal of Computational and Nonlinear Dynamics 87 46 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 81 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 107 81 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 413 81 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 78 101 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 190 84 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 Variational integration for robust data-driven inference of noisy and unstable dynamical systems Zhi-Qi Zhang, Pei Wang 2026-10-01 Nonlinear Dynamics 0 4
visibility_off Data-Driven Discovery of High-Dimensional Dynamical Systems with Sparse Interpretable Neural Networks S. Xing, Qing-Yu Han, E. Charalampidis, Ying-Cheng Lai 2026-09-29 PRX Intelligence 0 16
visibility_off SIPHy: Sparse identification of port-Hamiltonian systems from noisy data Håkon Noren Myhr, Sølve Eidnes, J. Kutz 2026-09-17 ArXiv 0 81
visibility_off Symbolic Neural ODEs: Learning interpretable models from time-series data N. Boddupalli, J. Moehlis 2026-08-22 ArXiv 0 7
visibility_off Data-Driven Modeling of Nonlinear Dynamical Systems with Machine Learning Ming-Yang Wang 2026-09-01 Theoretical and Natural Science 0 6
visibility_off Data-Driven Learning of Unknown Nonlinear Differential Equations Using Functional Analysis Seyyed Shaho Alaviani, Yong-Zhi Qu, G. Vogl 2026-09-03 ArXiv 0 6
visibility_off Stochastic Physics-Constrained Operator Inference for Complex Systems Chang-Hong Mou 2026-09-27 ArXiv 0 1
visibility_off Tensor sparse identification of differential equations of nonlinear dynamical systems Denis M. Tikhonov, V. Strijov 2026-09-11 Modeling and Analysis of Information Systems 0 9
visibility_off Higher-Order Kolmogorov-Arnold Networks for Dynamics Kevin Slote, Jeremie Fish 2026-10-02 ArXiv 0 6
visibility_off Tensor-Train Weak SINDy: Identifying High-Dimensional Nonlinear Dynamics W. Houser, Vanja Dukic, David M. Bortz 2026-09-08 ArXiv 0 6
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 Identifying ODEs from Unstructured Data with Causal Representation Learning Alessandro Trenta, Riccardo Massidda, D. Bacciu, Sara Magliacane 2026-09-29 ArXiv 0 29
visibility_off From Individual Trajectories to Population Densities: Weak-Form Inference of Heterogeneous Growth Laws Rainey Lyons, Vanja Dukic, David M. Bortz 2026-09-25 ArXiv 0 6
visibility_off Physiology-Informed Sparse Identification of Dynamic Crop Models Corné Verburg, Alexander Heinlein, F. van Eeuwijk, Neil V. Budko 2026-10-12 ArXiv 0 67
visibility_off Neural-Operator-Predicted Time-Dependent Reduced Subspaces for Projection-Based Simulation of Nonlinear PDEs Bo-Xi Song, Rennie Mirollo, J. Engelbrecht 2026-10-06 ArXiv 0 20
visibility_off Dynamics Creation through Neural Dynamical Transfer Learning Hekun Ma, Qi-Yang Ge, Yu Meng, C. Grebogi, Wei Lin 2026-09-09 ArXiv 0 25
visibility_off Gaussian process learning with flow map refinement for parameter estimation in dynamical systems Yue Hao, Dongwei Ye 2026-08-23 ArXiv 0 13
visibility_off NEXT: Physics-Informed Neuro-Spectral Exponential Time Differencing Architectures Márcio Marques, Leonardo Mendonça, Leonardo M. Moreira, Christian Júnior de Oliveira, Vitor Balestro, Tiago Novello, Daniel Yukimura, Pavel S. Petrov, Lucas Nissenbaum 2026-09-25 ArXiv 0 6
visibility_off Petrov-Galerkin operator inference with application to stability-encouraging identification J. Rettberg, Jonas Nicodemus, Harsh Sharma, Boris Kramer, Jörg Fehr, Benjamin Unger 2026-10-01 ArXiv 1 5
visibility_off Finite-Data Error Bounds for Approximating the Koopman Operator: Sampling Measures, Super-Polynomial Convergence and Regularization D. Fassler, Rachel Morris, Jason J. Bramburger, Simone Brugiapaglia 2026-09-25 ArXiv 0 14
visibility_off Symbolic regression enables coarse-grained model discovery of intracellular signalling dynamics Theodore de Pomereu, Fabian Fröhlich 2026-08-21 bioRxiv 0 23
visibility_off Practical Algebraic Parameter Estimation for Noisy Data via Gaussian Process Regression Oren Bassik, Alexander Demin, Alexey Ovchinnikov 2026-09-24 ArXiv 0 19
visibility_off Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions James Crowley, Faez Ahmed, A. van Beek 2026-08-31 ArXiv 0 9
visibility_off Automated discovery of dimensional reductions in coupled oscillators Dishant Sisodia, S. Jalan 2026-09-30 ArXiv 0 2
visibility_off Resolving Structural Uncertainty in Stochastic Dynamical Systems via Ensemble-Based Bayesian Inference Francesco Zambelli, Valeria d'Andrea, Manlio De Domenico 2026-10-14 ArXiv 0 16
visibility_off Spatio-temporal Latent Denoising Diffusion Probabilistic Models for Reduced-order Modeling of Parametrized Dynamical Systems Michiel Nikken, Nicolò Botteghi, Federico Califano, S. Glas 2026-09-15 ArXiv 0 9
visibility_off Learning Closure of Dynamical Systems with Kernel Ridge Regression Evan Habbershaw, Jonathan Harlim, Senwei Liang 2026-10-01 ArXiv 0 13
visibility_off Physics-Informed Nonlinear Vector Autoregressive Models for the Prediction of Dynamical Systems J. Adler, Samuel Hocking, Xiao-Zhe Hu, Shafiqul Islam 2026-09-30 SIAM Journal on Scientific Computing 0 24
visibility_off Physics-Informed Kolmogorov-Arnold networks for viscoelastic fluid equations Suryanshu Singh, Midhuna Suresh, Akanksha Gupta 2026-08-30 ArXiv 1 7
visibility_off An Adjoint Krylov Approach to Parameter Inference for Affine Families of Linear Evolution Equations Aditya Dendukuri, Shivkumar Chandrasekaran, Linda R. Petzold 2026-10-11 ArXiv 0 7
visibility_off A Practical Tutorial on Physics‐Informed Networks for Pharmacometrics and Quantitative Systems Pharmacology Nazanin Ahmadi Daryakenari, M. Kohandel 2026-09-22 CPT: Pharmacometrics & Systems Pharmacology 0 29
visibility_off Real-time inverse solutions via neural matrix operators Julie V. Pham, Thomas O'Leary-Roseberry, O. Ghattas, K. Willcox 2026-08-25 ArXiv 0 5
visibility_off How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions K. Rabiei, G. Rempała, R. Laubenbacher, Wen-Rui Hao 2026-09-03 Bulletin of Mathematical Biology 0 27
visibility_off Learning Long-Term Stable Operator Inference Reduced-Order Models of Fluid Flows through Online Spatial Filtering Ian Moore, Ping-Hsuan Tsai, Anthony Gruber, Ionut-Gabriel Farcas, Christopher R. Wentland, Irina Tezaur, T. Iliescu 2026-09-13 ArXiv 1 11
visibility_off Hyperparameter selection for equation learning with biologically-informed neural networks William Lavery, Jodie A. Cochrane, John T. Nardini, S. Hamis 2026-10-02 ArXiv 0 11
visibility_off Automatic denoising and differentiation based on Savitzky-Golay filtering and Homogeneous Differentiators for attractor reconstruction via differential embedding Uros Sutulovic, D. Proverbio, Rami Katz, G. Giordano 2026-09-16 ArXiv 0 4
visibility_off A wavelet-augmented time-domain minimum residual method for nonlinear systems with abrupt transitions Zhe-Lin Gong, Ji-Ke Liu, Zheng-Bo Yuan, Zhong-Yu Lu, Guang Liu 2026-09-01 Nonlinear Dynamics 0 23
visibility_off Identification and Recovery of Linear Dynamics from Partial Trajectories Le Gong 2026-10-03 ArXiv 0 3
visibility_off Neural Symbollic Regression Using Deep Learning and Sparse Modelling U. Ravikumar, S. Sumitra 2026-09-01 ArXiv 0 1
visibility_off Physics-Informed Stochastic Configuration Machine: A Backpropagation-Free Neural Network with Fast Training for Nonlinear Differential Equations Yueze Song, Zhong-Zhe Chen, Li-Hui Cen, Liang Wu, Kai Zhang School Of Automation, Central South University, Changsha, China, Johns Hopkins University, Baltimore, Usa, State Key Laboratory of Simulation, Regulation Of Water Cycle In River Basin, China Institute of Water Resources, Hydropower Research, Beijing 2026-08-27 ArXiv 0 23
visibility_off Functional dynamic mode decomposition: Learning infinite-dimensional systems from data Stefan Klus, Eirini Ioannou 2026-09-24 ArXiv 0 23
visibility_off Recovering Governing Dynamics from Distributed Observations via Exact Spline Merging N. Mysore 2026-09-15 ArXiv 0 8
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index