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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:

Physics-Informed Neural Network (PINN) Evolution and Beyond: A Systematic Literature Review and Bibliometric Analysis
Zaharaddeen Karami Lawal, Hayati Yassin, Daphne Teck Ching Lai, et al.
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 4, pp. 140-140
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

From PINNs to PIKANs: recent advances in physics-informed machine learning
Juan Diego Toscano, Vivek Oommen, Alan John Varghese, et al.
Machine learning for computational science and engineering (2025) Vol. 1, Iss. 1
Closed Access | Times Cited: 3
Physics-Informed Machine Learning for Data Anomaly Detection, Classification, Localization, and Mitigation: A Review, Challenges, and Path Forward
Mehdi Jabbari Zideh, Paroma Chatterjee, Anurag K. Srivastava
IEEE Access (2023) Vol. 12, pp. 4597-4617
Open Access | Times Cited: 26
Understanding Physics-Informed Neural Networks: Techniques, Applications, Trends, and Challenges
Amer Farea, Olli Yli‐Harja, Frank Emmert‐Streib
AI (2024) Vol. 5, Iss. 3, pp. 1534-1557
Open Access | Times Cited: 12
Gradient-annihilated PINNs for solving Riemann problems: Application to relativistic hydrodynamics
Antonio Ferrer-Sánchez, José D. Martín‐Guerrero, Roberto Ruiz de Austri-Bazan, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 424, pp. 116906-116906
Open Access | Times Cited: 11
Physics-infused deep neural network for solution of non-associative Drucker–Prager elastoplastic constitutive model
Arunabha M. Roy, Suman Guha, Veera Sundararaghavan, et al.
Journal of the Mechanics and Physics of Solids (2024) Vol. 185, pp. 105570-105570
Closed Access | Times Cited: 8
From data to insight, enhancing structural health monitoring using physics-informed machine learning and advanced data collection methods
Syed Haider Mehdi Rizvi, Muntazir Abbas
Engineering Research Express (2023) Vol. 5, Iss. 3, pp. 032003-032003
Open Access | Times Cited: 18
Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks
Stefano Berrone, C. Canuto, Moreno Pintore, et al.
Heliyon (2023) Vol. 9, Iss. 8, pp. e18820-e18820
Open Access | Times Cited: 17
Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines
Kamaljyoti Nath, Xuhui Meng, Daniel J. Smıth, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 16
Physics-guided training of GAN to improve accuracy in airfoil design synthesis
Kazunari Wada, Katsuyuki Suzuki, Kazuo Yonekura
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 421, pp. 116746-116746
Open Access | Times Cited: 7
Evolutionary probability density reconstruction of stochastic dynamic responses based on physics-aided deep learning
Zidong Xu, Hao Wang, Kaiyong Zhao, et al.
Reliability Engineering & System Safety (2024) Vol. 246, pp. 110081-110081
Closed Access | Times Cited: 7
Fractional rheology-informed neural networks for data-driven identification of viscoelastic constitutive models
Donya Dabiri, Milad Saadat, Deepak Mangal, et al.
Rheologica Acta (2023) Vol. 62, Iss. 10, pp. 557-568
Open Access | Times Cited: 14
Physics-Informed Neural Networks for solving transient unconfined groundwater flow
Daniele Secci, Vanessa A. Godoy, J. Jaime Gómez‐Hernández
Computers & Geosciences (2023) Vol. 182, pp. 105494-105494
Open Access | Times Cited: 14
Physics-based neural networks for the characterization and behavior assessment of construction materials
Ahed Habib, M. Talha Junaid, Salah Altoubat, et al.
Journal of Building Engineering (2025) Vol. 100, pp. 111788-111788
Closed Access
Research on pulse transmission dynamics in optical fiber based on intelligence algorithms
Jun Li, Jin Su, HAN Xiaoxiang, et al.
Acta Physica Sinica (2025) Vol. 74, Iss. 6
Open Access
Toward scalable prediction of indoor thermal dynamics: Neural-network-implanted state-space (NNiSS) model
Jeeye Mun, Hyeong-Gon Jo, Cheol Soo Park
Energy and Buildings (2025), pp. 115359-115359
Closed Access
A physics-informed neural network framework for laminated composite plates under bending
Weixi Wang, Huu‐Tai Thai
Thin-Walled Structures (2025), pp. 113014-113014
Open Access
Generative adversarial physics-informed neural networks for solving forward and inverse problem with small labeled samples
Wensheng Li, Chuncheng Wang, Hanting Guan, et al.
Computers & Mathematics with Applications (2025) Vol. 183, pp. 98-120
Closed Access
From traditional damage detection methods to Physics-Informed Machine Learning in bridges: A review
Safae Mammeri, Brais Barros, Borja Conde, et al.
Engineering Structures (2025) Vol. 330, pp. 119862-119862
Closed Access
Physics-Informed Neural Network for the Estimation of Bit Rotation Speed and Friction Parameters in Drilling
Hana Yahia, Florent Di Meglio, Bruno Figliuzzi, et al.
(2025)
Closed Access
Large deflection analysis of functionally graded reinforced sandwich beams with auxetic core using physics-informed neural network
Reza Nopour, Ali Fallah, M.M. Aghdam
Mechanics Based Design of Structures and Machines (2025), pp. 1-25
Closed Access
Surrogate-based Respiratory Motion Estimation using Physics-enhanced Implicit Neural Representations
Jan Boysen, Hristina Uzunova, Jan Ehrhardt, et al.
Informatik aktuell (2025), pp. 13-18
Closed Access
Using Physics-Informed neural networks for solving Navier-Stokes equations in fluid dynamic complex scenarios
Tommaso Botarelli, Marco Fanfani, Paolo Nesi, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110347-110347
Open Access
FE Reduced-Order Model-Informed Neural Operator for Structural Dynamic Response Prediction
Laihao Yang, Xinzhe Luo, Zhibo Yang, et al.
Neural Networks (2025), pp. 107437-107437
Closed Access
Physics‐Informed Extreme Learning Machine Applied for Eigenmode Analysis of Waveguides and Transmission Lines
Li Huang, Liang Chen, Rongchuan Bai
International Journal of RF and Microwave Computer-Aided Engineering (2025) Vol. 2025, Iss. 1
Open Access
An advanced deep learning framework for simulating information propagation dynamics
Yuewei Wu, Zhiqiang Zhang, Jian Wu, et al.
Frontiers in Physics (2025) Vol. 13
Open Access
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