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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Modern Koopman Theory for Dynamical Systems
Steven L. Brunton, Marko Budišić, Eurika Kaiser, et al.
SIAM Review (2022) Vol. 64, Iss. 2, pp. 229-340
Open Access | Times Cited: 263

Showing 1-25 of 263 citing articles:

Signal propagation in complex networks
Peng Ji, Jiachen Ye, Yu Mu, et al.
Physics Reports (2023) Vol. 1017, pp. 1-96
Open Access | Times Cited: 175
PySINDy: A comprehensive Python package for robust sparse system identification
Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, et al.
The Journal of Open Source Software (2022) Vol. 7, Iss. 69, pp. 3994-3994
Open Access | Times Cited: 113
Controlling complex networks with complex nodes
Raissa M. D’Souza, Mario di Bernardo, Yang‐Yu Liu
Nature Reviews Physics (2023) Vol. 5, Iss. 4, pp. 250-262
Closed Access | Times Cited: 61
Reconstructing computational system dynamics from neural data with recurrent neural networks
Daniel Durstewitz, Georgia Koppe, Max Ingo Thurm
Nature reviews. Neuroscience (2023) Vol. 24, Iss. 11, pp. 693-710
Closed Access | Times Cited: 45
The low-rank hypothesis of complex systems
Vincent Thibeault, Antoine Allard, Patrick Desrosiers
Nature Physics (2024) Vol. 20, Iss. 2, pp. 294-302
Closed Access | Times Cited: 23
Promising directions of machine learning for partial differential equations
Steven L. Brunton, J. Nathan Kutz
Nature Computational Science (2024) Vol. 4, Iss. 7, pp. 483-494
Closed Access | Times Cited: 19
Laplace neural operator for solving differential equations
Qianying Cao, Somdatta Goswami, George Em Karniadakis
Nature Machine Intelligence (2024) Vol. 6, Iss. 6, pp. 631-640
Closed Access | Times Cited: 17
Transformers for modeling physical systems
Nicholas Geneva, Nicholas Zabaras
Neural Networks (2021) Vol. 146, pp. 272-289
Open Access | Times Cited: 91
Deeptime: a Python library for machine learning dynamical models from time series data
Moritz Hoffmann, Martin K. Scherer, Tim Hempel, et al.
Machine Learning Science and Technology (2021) Vol. 3, Iss. 1, pp. 015009-015009
Open Access | Times Cited: 82
Physics-constrained, low-dimensional models for magnetohydrodynamics: First-principles and data-driven approaches
Alan A. Kaptanoglu, Kyle Morgan, C. Hansen, et al.
Physical review. E (2021) Vol. 104, Iss. 1
Open Access | Times Cited: 71
Deep Koopman Operator With Control for Nonlinear Systems
Haojie Shi, Max Q.‐H. Meng
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 3, pp. 7700-7707
Open Access | Times Cited: 54
Parsimony as the ultimate regularizer for physics-informed machine learning
J. Nathan Kutz, Steven L. Brunton
Nonlinear Dynamics (2022) Vol. 107, Iss. 3, pp. 1801-1817
Closed Access | Times Cited: 41
Residual dynamic mode decomposition: robust and verified Koopmanism
Matthew J. Colbrook, Lorna J. Ayton, Máté Szőke
Journal of Fluid Mechanics (2023) Vol. 955
Open Access | Times Cited: 37
Rigorous data‐driven computation of spectral properties of Koopman operators for dynamical systems
Matthew J. Colbrook, Alex Townsend
Communications on Pure and Applied Mathematics (2023) Vol. 77, Iss. 1, pp. 221-283
Open Access | Times Cited: 24
From snapshots to manifolds – a tale of shear flows
E. Farzamnik, Andrea Ianiro, Stefano Discetti, et al.
Journal of Fluid Mechanics (2023) Vol. 955
Open Access | Times Cited: 24
The mpEDMD Algorithm for Data-Driven Computations of Measure-Preserving Dynamical Systems
Matthew J. Colbrook
SIAM Journal on Numerical Analysis (2023) Vol. 61, Iss. 3, pp. 1585-1608
Open Access | Times Cited: 23
Behavioral theory for stochastic systems? A data-driven journey from Willems to Wiener and back again
Timm Faulwasser, Ruchuan Ou, Guanru Pan, et al.
Annual Reviews in Control (2023) Vol. 55, pp. 92-117
Open Access | Times Cited: 22
Koopman form of nonlinear systems with inputs
Lucian Cristian Iacob, Roland Tóth, Maarten Schoukens
Automatica (2024) Vol. 162, pp. 111525-111525
Open Access | Times Cited: 12
Generative learning for nonlinear dynamics
William Gilpin
Nature Reviews Physics (2024) Vol. 6, Iss. 3, pp. 194-206
Closed Access | Times Cited: 11
A review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 11
Error bounds for kernel-based approximations of the Koopman operator
Friedrich Philipp, Manuel Schaller, Karl Worthmann, et al.
Applied and Computational Harmonic Analysis (2024) Vol. 71, pp. 101657-101657
Open Access | Times Cited: 11
Koopman neural operator as a mesh-free solver of non-linear partial differential equations
Wei Xiong, Xiaomeng Huang, Ziyang Zhang, et al.
Journal of Computational Physics (2024) Vol. 513, pp. 113194-113194
Open Access | Times Cited: 8
Learning global linear representations of nonlinear dynamics
Thomas Breunung, Florian Kogelbauer
Nonlinear Dynamics (2025)
Open Access | Times Cited: 1
Dictionary-Free Koopman Model Predictive Control with Nonlinear Input Transformation
Vít Cibulka, Milan Korda, Tomáš Haniš
SIAM Journal on Applied Dynamical Systems (2025) Vol. 24, Iss. 1, pp. 94-130
Open Access | Times Cited: 1
SINDy with Control: A Tutorial
Urban Fasel, Eurika Kaiser, J. Nathan Kutz, et al.
2021 60th IEEE Conference on Decision and Control (CDC) (2021), pp. 16-21
Closed Access | Times Cited: 45
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