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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:

Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next
Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo, et al.
Journal of Scientific Computing (2022) Vol. 92, Iss. 3
Open Access | Times Cited: 1065

Showing 1-25 of 1065 citing articles:

Physics-Informed Attention Temporal Convolutional Network for EEG-Based Motor Imagery Classification
Hamdi Altaheri, Ghulam Muhammad, Mansour Alsulaiman
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 2, pp. 2249-2258
Closed Access | Times Cited: 187
Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
Ben Moseley, Andrew Markham, Tarje Nissen‐Meyer
Advances in Computational Mathematics (2023) Vol. 49, Iss. 4
Open Access | Times Cited: 138
Transfer learning based physics-informed neural networks for solving inverse problems in engineering structures under different loading scenarios
Xu Chen, Ba Trung Cao, Yong Yuan, et al.
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 405, pp. 115852-115852
Open Access | Times Cited: 116
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
Venkat Pavan Nemani, Luca Biggio, Xun Huan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 205, pp. 110796-110796
Open Access | Times Cited: 82
Can physics-informed neural networks beat the finite element method?
Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz, et al.
IMA Journal of Applied Mathematics (2024) Vol. 89, Iss. 1, pp. 143-174
Open Access | Times Cited: 77
Physics-informed neural networks as surrogate models of hydrodynamic simulators
James Donnelly, Alireza Daneshkhah, Soroush Abolfathi
The Science of The Total Environment (2023) Vol. 912, pp. 168814-168814
Open Access | Times Cited: 75
Masked Swin Transformer Unet for Industrial Anomaly Detection
Jielin Jiang, Jiale Zhu, Muhammad Bilal, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 2, pp. 2200-2209
Closed Access | Times Cited: 73
Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Doksoo Lee, Wei Chen, Liwei Wang, et al.
Advanced Materials (2023) Vol. 36, Iss. 8
Open Access | Times Cited: 72
Data-driven science and machine learning methods in laser–plasma physics
A. Döpp, Christoph Eberle, Sunny Howard, et al.
High Power Laser Science and Engineering (2023) Vol. 11
Open Access | Times Cited: 57
Dynamic analysis on optical pulses via modified PINNs: Soliton solutions, rogue waves and parameter discovery of the CQ-NLSE
Yu-Hang Yin, Xing Lü
Communications in Nonlinear Science and Numerical Simulation (2023) Vol. 126, pp. 107441-107441
Closed Access | Times Cited: 51
Accelerating the design of compositionally complex materials via physics-informed artificial intelligence
Dierk Raabe, Jaber Rezaei Mianroodi, Jörg Neugebauer
Nature Computational Science (2023) Vol. 3, Iss. 3, pp. 198-209
Closed Access | Times Cited: 48
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics
Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, et al.
Journal of Computing and Information Science in Engineering (2024) Vol. 24, Iss. 4
Closed Access | Times Cited: 48
Data-driven solitons and parameter discovery to the (2+1)-dimensional NLSE in optical fiber communications
Xue Peng, Yiwei Zhao, Xing Lü
Nonlinear Dynamics (2023) Vol. 112, Iss. 2, pp. 1291-1306
Closed Access | Times Cited: 46
Machine learning for numerical weather and climate modelling: a review
Catherine de Burgh-Day, Tennessee Leeuwenburg
Geoscientific model development (2023) Vol. 16, Iss. 22, pp. 6433-6477
Open Access | Times Cited: 45
Roadmap on photonic metasurfaces
Sebastian A. Schulz, Rupert F. Oulton, Mitchell Kenney, et al.
Applied Physics Letters (2024) Vol. 124, Iss. 26
Open Access | Times Cited: 41
Deep learning in computational mechanics: a review
Leon Herrmann, Stefan Kollmannsberger
Computational Mechanics (2024) Vol. 74, Iss. 2, pp. 281-331
Open Access | Times Cited: 28
Multilevel domain decomposition-based architectures for physics-informed neural networks
Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 429, pp. 117116-117116
Open Access | Times Cited: 26
Physics-informed deep learning for multi-species membrane separations
Danyal Rehman, John H. Lienhard
Chemical Engineering Journal (2024) Vol. 485, pp. 149806-149806
Closed Access | Times Cited: 25
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations
Nick McGreivy, Ammar Hakim
Nature Machine Intelligence (2024) Vol. 6, Iss. 10, pp. 1256-1269
Closed Access | Times Cited: 25
A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation
Wenbo Cao, Jiahao Song, Weiwei Zhang
Physics of Fluids (2024) Vol. 36, Iss. 2
Open Access | Times Cited: 21
KAN-ODEs: Kolmogorov–Arnold network ordinary differential equations for learning dynamical systems and hidden physics
Benjamin C. Koenig, Suyong Kim, Sili Deng
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 432, pp. 117397-117397
Closed Access | Times Cited: 20
Methods for enabling real-time analysis in digital twins: A literature review
Mohammad Sadegh Es-haghi, Cosmin Anitescu, Timon Rabczuk
Computers & Structures (2024) Vol. 297, pp. 107342-107342
Open Access | Times Cited: 19
Damage identification for plate structures using physics-informed neural networks
Wei Zhou, Y. F. Xu
Mechanical Systems and Signal Processing (2024) Vol. 209, pp. 111111-111111
Closed Access | Times Cited: 18
Terahertz nanoscopy: Advances, challenges, and the road ahead
Xiao Guo, Karl Bertling, Bogdan C. Donose, et al.
Applied Physics Reviews (2024) Vol. 11, Iss. 2
Open Access | Times Cited: 18
Physics-informed ConvNet: Learning physical field from a shallow neural network
Pengpeng Shi, Zhi Zeng, Tianshou Liang
Communications in Nonlinear Science and Numerical Simulation (2024) Vol. 132, pp. 107911-107911
Open Access | Times Cited: 17
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