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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 Networks and Functional Interpolation for Data-Driven Parameters Discovery of Epidemiological Compartmental Models
Enrico Schiassi, Mario De Florio, Andrea D’Ambrosio, et al.
Mathematics (2021) Vol. 9, Iss. 17, pp. 2069-2069
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Extreme theory of functional connections: A fast physics-informed neural network method for solving ordinary and partial differential equations
Enrico Schiassi, Roberto Furfaro, Carl Leake, et al.
Neurocomputing (2021) Vol. 457, pp. 334-356
Open Access | Times Cited: 133
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: 71
AI-Aristotle: A physics-informed framework for systems biology gray-box identification
Nazanin Ahmadi Daryakenari, Mario De Florio, Khemraj Shukla, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 3, pp. e1011916-e1011916
Open Access | Times Cited: 22
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: 5
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology
Mario De Florio, Zongren Zou, Daniele E. Schiavazzi, et al.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2025) Vol. 383, Iss. 2292
Open Access | Times Cited: 2
Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges
Yang Ye, Abhishek Pandey, Carolyn E. Bawden, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 2
Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley–Leverett problem
Ruben Rodriguez-Torrado, Pablo Jácome Ruiz, Luis Cueto‐Felgueroso, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 56
Physics-informed neural networks and functional interpolation for stiff chemical kinetics
Mario De Florio, Enrico Schiassi, Roberto Furfaro
Chaos An Interdisciplinary Journal of Nonlinear Science (2022) Vol. 32, Iss. 6
Closed Access | Times Cited: 43
Physics-informed neural networks for rarefied-gas dynamics: Thermal creep flow in the Bhatnagar–Gross–Krook approximation
Mario De Florio, Enrico Schiassi, B. D. Ganapol, et al.
Physics of Fluids (2021) Vol. 33, Iss. 4
Closed Access | Times Cited: 52
Investigating molecular transport in the human brain from MRI with physics-informed neural networks
Bastian Zapf, Johannes Haubner, Miroslav Kuchta, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 32
Physics-Informed Neural Networks for Optimal Planar Orbit Transfers
Enrico Schiassi, Andrea D’Ambrosio, Kristofer Drozd, et al.
Journal of Spacecraft and Rockets (2022) Vol. 59, Iss. 3, pp. 834-849
Closed Access | Times Cited: 30
Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients
Mario De Florio, Enrico Schiassi, Francesco Calabrò, et al.
Journal of Computational and Applied Mathematics (2023) Vol. 436, pp. 115396-115396
Open Access | Times Cited: 22
Learning Fuel-Optimal Trajectories for Space Applications via Pontryagin Neural Networks
Andrea D’Ambrosio, Roberto Furfaro
Aerospace (2024) Vol. 11, Iss. 3, pp. 228-228
Open Access | Times Cited: 8
Fluidized Bed Scale-Up for Sustainability Challenges. 2. New Pathway
Jia Wei Chew, Ray Cocco
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 18, pp. 8025-8043
Open Access | Times Cited: 6
Nonlinear discrete-time observers with Physics-Informed Neural Networks
Héctor Vargas, Gianluca Fabiani, Nikolaos Kazantzis, et al.
Chaos Solitons & Fractals (2024) Vol. 186, pp. 115215-115215
Open Access | Times Cited: 6
Physics informed neural network based scheme and its error analysis for ψ-Caputo type fractional differential equations
S M Sivalingam, V. Govindaraj
Physica Scripta (2024) Vol. 99, Iss. 9, pp. 096002-096002
Closed Access | Times Cited: 6
Dynamic Malware Mitigation Strategies for IoT Networks: A Mathematical Epidemiology Approach
Roberto Casado‐Vara, Marcos Severt, Antonio Díaz-Longueira, et al.
Mathematics (2024) Vol. 12, Iss. 2, pp. 250-250
Open Access | Times Cited: 5
Coefficient identification in a SIS fractional-order modelling of economic losses in the propagation of COVID-19
Slavi Georgiev, Lubin G. Vulkov
Journal of Computational Science (2023) Vol. 69, pp. 102007-102007
Open Access | Times Cited: 11
A Physics-Informed Neural Network approach for compartmental epidemiological models
Caterina Millevoi, Damiano Pasetto, Massimiliano Ferronato
PLoS Computational Biology (2024) Vol. 20, Iss. 9, pp. e1012387-e1012387
Open Access | Times Cited: 4
Physics-Informed Pontryagin Neural Networks for Path-Constrained Optimal Control Problems
Andrea D’Ambrosio, Boris Benedikter, Roberto Furfaro
AIAA SCITECH 2022 Forum (2025)
Closed Access
Rocket Ascent Trajectory Optimization via Physics-Informed Pontryagin Neural Networks
Boris Benedikter, Andrea D’Ambrosio, Roberto Furfaro
AIAA SCITECH 2022 Forum (2025)
Closed Access
Theory of functional connections applied to quadratic and nonlinear programming under equality constraints
Tina Mai, Daniele Mortari
Journal of Computational and Applied Mathematics (2021) Vol. 406, pp. 113912-113912
Open Access | Times Cited: 26
Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems
Andrea D’Ambrosio, Enrico Schiassi, Fabio Curti, et al.
Mathematics (2021) Vol. 9, Iss. 9, pp. 996-996
Open Access | Times Cited: 25
Physics-Informed Neural Networks for rarefied-gas dynamics: Poiseuille flow in the BGK approximation
Mario De Florio, Enrico Schiassi, B. D. Ganapol, et al.
Zeitschrift für angewandte Mathematik und Physik (2022) Vol. 73, Iss. 3
Closed Access | Times Cited: 14
A Physic-Informed Neural Network Approach to Orbit Determination
Andrea Scorsoglio, Luca Ghilardi, Roberto Furfaro
The Journal of the Astronautical Sciences (2023) Vol. 70, Iss. 4
Closed Access | Times Cited: 7
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