Symbolic regression

This page was last updated on 2026-10-12 06:46:12 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 5602 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 160 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 1094 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 679 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. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 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 442 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. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 412 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 86 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. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A 409 81 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 77 101 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 189 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 Differential-Embedding Reconstruction of Dynamical Systems from Scalar Time Series A. Shaa, C. Guet 2026-08-17 ArXiv 0 12
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 Linearized PINN with pretrained nonlinear layers Wen-Hao Chen, Alexandre M. Tartakovsky 2026-09-14 ArXiv 0 4
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 0 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 J. 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 Bilevel optimization for data-driven learning of Koopman embeddings using kernel-based autoencoders J. N. N'konzi, F. Nüske, Stefan Klus 2026-10-08 ArXiv 0 18
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 Learning piecewise-smooth dynamical systems D. Murari, Erik Jansson, Chris Budd Obe, C. Schönlieb 2026-08-20 ArXiv 0 57
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 A Practical Tutorial on Physics‐Informed Networks for Pharmacometrics and Quantitative Systems Pharmacology Nazanin Ahmadi Daryakenari, Mohammad Kohandel 2026-09-22 CPT: Pharmacometrics & Systems Pharmacology 0 5
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 Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data Jule Budnick, Andrew Keane, Serhiy Yanchuk 2026-09-21 ArXiv 0 39
visibility_off How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions Kobra Rabiei, G. Rempała, R. Laubenbacher, Wen-Rui Hao 2026-09-03 Bulletin of Mathematical Biology 0 27
visibility_off Causal Local States: Scalable Simultaneous Causal Network Inference and Forecasting for Dynamical Systems J. Braun, Fabian Fischbach, , Sebastian Baur, C. Räth 2026-08-18 ArXiv 1 23
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 Inertial Manifold Neural Operator for Dissipative Time-Dependent Partial Differential Equations Xiaoyan Xie, Clarence W. Rowley 2026-08-24 ArXiv 0 3
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 Physics-Informed Learning of Feedback-Linearizing Representations Pavlos Kallinikidis, Feng-Jun Yang, David Snyder, Jacob H. Seidman, Nikolai Matni, P. Perdikaris, George J. Pappas 2026-09-26 ArXiv 0 57
visibility_off Learning Koopman prediction for the Caputo fractional-order systems with unknown nonlinear terms via auxiliary variables Fan-Hai Ou Yang, Jin-Rong Wang 2026-10-01 Nonlinear Dynamics 0 58
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
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index