Symbolic regression

This page was last updated on 2024-09-16 06:06:54 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 3270 65 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 87 23 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 620 65 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 452 65 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 435 65 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 321 65 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 205 65 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 62 77 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 32 65 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 71 65 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 164 65 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 29 91 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 116 65 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 Discovering Governing equations from Graph-Structured Data by Sparse Identification of Nonlinear Dynamical Systems Mohammad Amin Basiri, Sina Khanmohammadi 2024-09-02 ArXiv 0 3
visibility_off Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems Shane A. McQuarrie, Anirban Chaudhuri, Karen Willcox, Mengwu Guo 2024-08-06 ArXiv 0 6
visibility_off Data-driven Discovery of Delay Differential Equations with Discrete Delays Alessandro Pecile, N. Demo, M. Tezzele, G. Rozza, Dimitri Breda 2024-07-29 ArXiv 1 50
visibility_off BINDy -- Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte-Carlo M.D. Champneys, T. J. Rogers 2024-08-15 ArXiv 0 1
visibility_off Spectrally Informed Learning of Fluid Flows Benjamin D. Shaffer, Jeremy R. Vorenberg, M. A. Hsieh 2024-08-26 ArXiv 0 2
visibility_off Quasi-potential and drift decomposition in stochastic systems by sparse identification Leonardo Grigorio, Mnerh Alqahtani 2024-09-10 ArXiv 0 1
visibility_off Learning Networked Dynamical System Models with Weak Form and Graph Neural Networks Yin Yu, Daning Huang, Seho Park, H. Pangborn 2024-07-23 ArXiv 0 11
visibility_off Solving Oscillator Ordinary Differential Equations via Soft-constrained Physics-informed Neural Network with Small Data Kai-liang Lu, Yu-meng Su, Zhuo Bi, Cheng Qiu, Wen-jun Zhang 2024-08-19 ArXiv 0 0
visibility_off Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam (Sankar) Alagapan, Adam S. Charles, Christopher J. Rozell 2024-08-29 ArXiv 0 19
visibility_off Physics-informed nonlinear vector autoregressive models for the prediction of dynamical systems James H. Adler, Samuel Hocking, Xiaozhe Hu, Shafiqul Islam 2024-07-25 ArXiv 0 2
visibility_off Learning Noise-Robust Stable Koopman Operator for Control with Physics-Informed Observables Shahriar Akbar Sakib, Shaowu Pan 2024-08-13 ArXiv 0 0
visibility_off Accurate data‐driven surrogates of dynamical systems for forward propagation of uncertainty Saibal De, Reese E. Jones, H. Kolla 2024-08-03 International Journal for Numerical Methods in Engineering 0 30
visibility_off Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery Pongpisit Thanasutives, Ken-ichi Fukui 2024-08-15 ArXiv 0 3
visibility_off Stable Sparse Operator Inference for Nonlinear Structural Dynamics P. D. Boef, Diana Manvelyan, Jos Maubach, W. Schilders, N. Wouw 2024-07-31 ArXiv 0 47
visibility_off Koopman Operators in Robot Learning Lu Shi, Masih Haseli, Giorgos Mamakoukas, Daniel Bruder, Ian Abraham, Todd Murphey, Jorge Cortes, Konstantinos Karydis 2024-08-08 ArXiv 0 9
visibility_off Learning Latent Space Dynamics with Model-Form Uncertainties: A Stochastic Reduced-Order Modeling Approach Jin Yi Yong, Rudy Geelen, Johann Guilleminot 2024-08-30 ArXiv 0 1
visibility_off Relaxation-based schemes for on-the-fly parameter estimation in dissipative dynamical systems Vincent R. Martinez, Jacob Murri, J. Whitehead 2024-08-26 ArXiv 0 1
visibility_off A PINN approach for the online identification and control of unknown PDEs Alessandro Alla, Giulia Bertaglia, Elisa Calzola 2024-08-06 ArXiv 0 1
visibility_off Sparse identification of time delay systems via pseudospectral collocation Enrico Bozzo, Dimitri Breda, Muhammad Tanveer 2024-08-04 ArXiv 0 0
visibility_off Data-driven identification of latent port-Hamiltonian systems J. Rettberg, Jonas Kneifl, Julius Herb, Patrick Buchfink, J. Fehr, B. Haasdonk 2024-08-15 ArXiv 0 32
visibility_off Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator Xinghao Dong, Chuanqi Chen, Jin-Long Wu 2024-08-06 ArXiv 1 2
visibility_off Data-driven ODE modeling of the high-frequency complex dynamics of a fluid flow Natsuki Tsutsumi, Kengo Nakai, Yoshitaka Saiki 2024-09-01 ArXiv 0 4
visibility_off Learning Stable Evolutionary PDE Dynamics: A Scalable System Identification Approach Diyou Liu, Mohammad Khosravi 2024-08-21 2024 IEEE Conference on Control Technology and Applications (CCTA) 0 0
visibility_off Sampling parameters of ordinary differential equations with Langevin dynamics that satisfy constraints Chris Chi, J. Weare, Aaron R Dinner 2024-08-28 ArXiv 0 20
visibility_off Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems Amber Hu, D. Zoltowski, Aditya Nair, David Anderson, Lea Duncker, Scott W. Linderman 2024-07-19 ArXiv 0 27
visibility_off Higher order quantum reservoir computing for non-intrusive reduced-order models Vinamr Jain, R. Maulik 2024-07-31 ArXiv 0 22
visibility_off On latent dynamics learning in nonlinear reduced order modeling N. Farenga, S. Fresca, Simone Brivio, A. Manzoni 2024-08-27 ArXiv 0 11
visibility_off Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators Chuwei Wang, Julius Berner, Zong-Yi Li, Di Zhou, Jiayun Wang, Jane Bae, A. Anandkumar 2024-08-09 ArXiv 0 18
visibility_off Predicting multi-parametric dynamics of externally forced oscillators using reservoir computing and minimal data Manish Yadav, Swati Chauhan, M. Shrimali, M. Stender 2024-08-27 ArXiv 0 19
visibility_off Enhancing spectral analysis in nonlinear dynamics with pseudoeigenfunctions from continuous spectra Itsushi Sakata, Yoshinobu Kawahara 2024-08-20 Scientific Reports 0 8
visibility_off Latent-EnSF: A Latent Ensemble Score Filter for High-Dimensional Data Assimilation with Sparse Observation Data Phillip Si, Peng Chen 2024-08-29 ArXiv 0 0
visibility_off Stochastic Neural Simulator for Generalizing Dynamical Systems across Environments Liu Jiaqi, Jiaxu Cui, Jiayi Yang, Bo Yang 2024-08-01 Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence 0 5
visibility_off Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling Mingxue Yan, Minghao Han, A. Law, Xunyuan Yin 2024-08-07 ArXiv 0 35
visibility_off Neural Ordinary Differential Equations for Model Order Reduction of Stiff Systems Matteo Caldana, J. Hesthaven 2024-08-12 ArXiv 0 64
visibility_off Optimal Experimental Design for Universal Differential Equations Christoph Plate, Carl Julius Martensen, Sebastian Sager 2024-08-13 ArXiv 0 1
visibility_off State Space Kriging model for emulating complex nonlinear dynamical systems under stochastic excitation Kai Chenga, Iason Papaioannoua, MengZe Lyub, Daniel Straub 2024-09-04 ArXiv 0 0
visibility_off A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations A. Aghaei 2024-09-05 ArXiv 0 5
visibility_off Physics-informed Discovery of State Variables in Second-Order and Hamiltonian Systems Félix Chavelli, Zi-Yu Khoo, Dawen Wu, Jonathan Sze Choong Low, Stéphane Bressan 2024-08-21 ArXiv 0 3
visibility_off Practical Guidelines for Data-driven Identification of Lifted Linear Predictors for Control Loi Do, Adam Uchytil, Zdenvek Hur'ak 2024-08-02 ArXiv 1 2
visibility_off Model free data assimilation with Takens embedding Ziyi Wang, Lijian Jiang 2024-08-16 ArXiv 0 0
visibility_off Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach Daniel Lengyel, P. Parpas, B. Hamzi, H. Owhadi 2024-08-12 ArXiv 0 37
visibility_off 4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models Kylen Solvik, Stephen G. Penny, Stephan Hoyer 2024-08-05 ArXiv 0 10
visibility_off Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots Théo Bourdais, Pau Batlle, Xianjin Yang, Ricardo Baptista, Nicolas Rouquette, H. Owhadi 2024-08-01 Proceedings of the National Academy of Sciences of the United States of America 0 37
visibility_off Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems Yuan Chen, Dongbin Xiu 2024-08-27 ArXiv 0 1
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index