Symbolic regression

This page was last updated on 2026-09-28 06:43:01 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 of the United States of America, Proceedings of the National Academy of Sciences 5501 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 158 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 1071 80 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 674 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 705 80 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 441 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 404 80 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 85 45 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 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 107 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 of the Royal Society A, Proceedings. Mathematical, Physical, and Engineering Sciences 402 80 open_in_new
visibility_off Learning sparse nonlinear dynamics via mixed-integer optimization D. Bertsimas, Wes Gurnee 2022-06-01 Nonlinear Dynamics 75 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 189 79 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 Dynamics-aware identification of governing equations from sparse and noisy data Pongpisit Thanasutives, Yoshinobu Kawahara 2026-07-31 ArXiv 1 11
visibility_off SIPHy: Sparse identification of port-Hamiltonian systems from noisy data Håkon Noren Myhr, Sølve Eidnes, J. Kutz 2026-09-17 ArXiv 0 80
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 linear analysis of dynamical systems via nonlinearity-subtracted dynamic mode decomposition Benjamín Herrmann, Katherine Cao, S. Brunton, B. McKeon 2026-08-13 ArXiv 0 77
visibility_off Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration S. Roman, L. Todorovski, S. Džeroski 2026-08-13 ArXiv 0 65
visibility_off Data-Driven Modeling of Nonlinear Dynamical Systems with Machine Learning Ming-Yang Wang 2026-09-01 Theoretical and Natural Science 0 5
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 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 A Sobolev–Information Perspective on Derivative-Observation-Augmented PINNs for Parameter Identification of Second-Order Dynamical Systems Liwen Xu, Yi-Xuan Lin 2026-08-09 Axioms 0 3
visibility_off Dynamic Reduced-Order Data Assimilation from Sparse Velocity Measurements Mauricio Portilla, F. Galarce, Ernesto Castillo, Benjamín Herrmann 2026-09-09 ArXiv 0 7
visibility_off Autoencoders vs. Numerical Analysis--Informed Manifold Learning for Navier--Stokes Flows A. Della Pia, Lucia Russo, I. Kevrekidis, Constantinos I. Siettos 2026-09-21 ArXiv 0 7
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 10
visibility_off Observable-Reduction-Guided Sparse Regression for Partially Observed Active-Quiescent Systems Kyle C. Nguyen, Kevin B. Flores 2026-08-11 ArXiv 0 3
visibility_off Identification of Nonlinear Dynamic Networks via Integral-Based Sparse Bayesian Learning and Stability Screening Yi-Ge Yao, Yao-Zhong Zheng, Ran Shi, Hai-Tao Zhang 2026-08-01 2026 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM) 0 3
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 SPIRAL-PO: Symbolic Identification of Partially Observed Nonlinear Dynamics with Application to Rotating Machinery Mohammad A. Ayoubi, Sina Piramoon 2026-08-01 ArXiv 0 2
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 Tensor-Train Weak SINDy: Identifying High-Dimensional Nonlinear Dynamics W. Houser, Vanja Dukic, David M. Bortz 2026-09-08 ArXiv 0 4
visibility_off Freeze, Then Select: Structured Field Adapters and Stability-Validated Weak Selection for PDE Discovery from Sparse Observations Juncheng Zhong, Chen Shen, Jian-Feng Liu, Z. Xiao, Longjiu Luo, Qianrong Wang, Wenjun Xu, Wenlian Lu 2026-07-31 ArXiv 0 5
visibility_off Linearized PINN with pretrained nonlinear layers Wen-Hao Chen, Alexandre M. Tartakovsky 2026-09-14 ArXiv 0 3
visibility_off Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis I. Guevara, Ye-Ping Hu 2026-07-31 ArXiv 0 2
visibility_off Koopman-based model predictive control for nonlinear systems with bounded model uncertainty Yang-Zhe Liu, Hanqiu Bao 2026-08-25 International Journal of Dynamics and Control 0 7
visibility_off Reconstructing fluid velocity fields from sparse sensors using a variational quantum algorithm N. Nguyen, M. M. Akash, K. Shoele, Yan-Zhu Chen, Hui-Xuan Wu 2026-09-08 ArXiv 0 18
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 12
visibility_off KOOPMAN-Luenberger Observer Design for Nonlinear Systems with Application to the Monitoring of a Latent Thermal Energy Storage Mustapha Habib, Dario Aguiar, Esther Kieseritzky, T. Barz, Qian Wang 2026-08-11 ArXiv 0 22
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 8
visibility_off Decoder-free operator autoencoder for reduced-order modeling of dynamical systems Xuan-Dong Lu, Yongming Liu 2026-08-04 Machine Learning for Computational Science and Engineering 1 11
visibility_off Going with the flow to solve for symmetry-driven PDE dynamics with physics-informed neural networks M. Kavousanakis, Gianluca Fabiani, A. Georgiou, Constantinos I. Siettos, P. Kevrekidis, I. Kevrekidis 2026-08-05 Nature Communications 1 53
visibility_off Physics-Integrated Operator Learning via Gaussian Splatting Representations Ji-Hao Zhang, Jun-Yi Guo, Jian-Xun Wang 2026-08-25 ArXiv 0 6
visibility_off Learning piecewise-smooth dynamical systems D. Murari, Erik Jansson, Chris Budd Obe, C. Schönlieb 2026-08-20 ArXiv 0 56
visibility_off Knowledge-Guided Physics-Informed Hybrid Learning Framework for Uncertainty-Aware Digital Twin Modeling of Nonlinear Thermal Power Systems Shymaa Darwish, Mohamed El-Habrouk, A. S. Abdel-Khalik, Ragi R. Hamdy 2026-08-13 Machine Learning and Knowledge Extraction 0 3
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 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 4
visibility_off Discovering Explicit Magnetic Core Loss Equations via Learnable Symbolic Sparse Identification Haoyu Wang, Jialin Zheng, Yihao Wu, Ziyang Xu, Alex J. Hanson 2026-08-01 ArXiv 0 14
visibility_off Real-time inverse solutions via neural matrix operators Julie V. Pham, Thomas O’Leary-Roseberry, Omar 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 36
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
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 25
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 0 23
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index