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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:

Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems
Junming Duan, Jan S. Hesthaven
Journal of Computational Physics (2023) Vol. 497, pp. 112621-112621
Open Access | Times Cited: 15

Showing 15 citing articles:

On latent dynamics learning in nonlinear reduced order modeling
N. Farenga, Stefania Fresca, Simone Brivio, et al.
Neural Networks (2025) Vol. 185, pp. 107146-107146
Open Access
Improved Greedy Identification of latent dynamics with application to fluid flows
Ayoub Razouk, Mourad Oulghelou, Peter J. Schmid
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 437, pp. 117799-117799
Closed Access
Data-Driven Distance Education Course Design: Content Recommendation Based on Big Data
Shu Min Wan, Yuerong Zhang
Smart innovation, systems and technologies (2025), pp. 461-471
Closed Access
A new hybrid reduced order modeling for parametrized Navier–Stokes equations in stream-vorticity formulation
Tao Zhang, Hui Xu, Lei Guo, et al.
Physics of Fluids (2024) Vol. 36, Iss. 6
Closed Access | Times Cited: 3
Domain decomposition for physics-data combined neural network based parametric reduced order modelling
Xinyu Pan, Dunhui Xiao
Journal of Computational Physics (2024) Vol. 519, pp. 113452-113452
Closed Access | Times Cited: 2
Error estimate of the Non-Intrusive Reduced Basis (NIRB) two-grid method with parabolic equations
Elise Grosjean, Yvon Maday
SMAI Journal of Computational Mathematics (2023) Vol. 9, pp. 227-256
Open Access | Times Cited: 4
Non-Intrusive Reduced-Order Modeling Based on Parametrized Proper Orthogonal Decomposition
Teng Li, Tianyu Pan, Xiangxin Zhou, et al.
Energies (2023) Vol. 17, Iss. 1, pp. 146-146
Open Access | Times Cited: 4
Data-Driven Reduced Order Surrogate Modeling for Coronary In-Stent Restenosis
Jianye Shi, Kiran Manjunatha, Felix Vogt, et al.
(2024)
Closed Access
A Modified Podi-Rbf Method to Improve the Accuracy of Local Solutions for Real-Time Finite Element Simulations of Indenter Contact Problems
Hyeon-Gyeong Lee, Hyun‐Gyu Kim
(2024)
Closed Access
Polytopic Autoencoders with Smooth Clustering for Reduced-order Modelling of Flows
Jan Heiland, Yongho Kim
Journal of Computational Physics (2024), pp. 113526-113526
Open Access
Data-driven reduced order surrogate modeling for coronary in-stent restenosis
Jianye Shi, Kiran Manjunatha, Felix Vogt, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 257, pp. 108466-108466
Open Access
A modified PODI-RBF method to improve the accuracy of local solutions for real-time finite element simulations of indenter contact problems
Hyeon-Gyeong Lee, Hyun‐Gyu Kim
Advances in Engineering Software (2024) Vol. 199, pp. 103806-103806
Closed Access
A data-driven reduced-order modeling approach for parameterized time-domain Maxwell's equations
Mengjun Yu, Kun Li
Networks and Heterogeneous Media (2024) Vol. 19, Iss. 3, pp. 1309-1335
Open Access
Advances in Data-Driven Reduced Order Models Using Two-Stage Dimension Reduction for Coupled Viscous Flow and Transport
Roberto Velho, Adriano Cortês, Gabriel F. Barros, et al.
(2024)
Closed Access
Adaptive Data-Driven Probabilistic Reduced-Order Models for Parameterized Dynamical Systems
Kai Cheng, Ralf Zimmermann
(2023)
Closed Access
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