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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:

Discovering a reaction–diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression
Zhen Zhang, Zongren Zou, Ellen Kuhl, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 419, pp. 116647-116647
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Correcting model misspecification in physics-informed neural networks (PINNs)
Zongren Zou, Xuhui Meng, George Em Karniadakis
Journal of Computational Physics (2024) Vol. 505, pp. 112918-112918
Open Access | Times Cited: 23
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: 21
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks
Khemraj Shukla, Juan Diego Toscano, Zhicheng Wang, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 431, pp. 117290-117290
Open Access | Times Cited: 16
Mathematical models on Alzheimer's disease and its treatment: A review
Mitali Maji, Subhas Khajanchi
Physics of Life Reviews (2025) Vol. 52, pp. 207-244
Closed Access | Times Cited: 3
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
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
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
Leveraging Multitime Hamilton–Jacobi PDEs for Certain Scientific Machine Learning Problems
Paula Chen, Tingwei Meng, Zongren Zou, et al.
SIAM Journal on Scientific Computing (2024) Vol. 46, Iss. 2, pp. C216-C248
Open Access | Times Cited: 8
Leveraging Viscous Hamilton–Jacobi PDEs for Uncertainty Quantification in Scientific Machine Learning
Zongren Zou, Tingwei Meng, Paula Chen, et al.
SIAM/ASA Journal on Uncertainty Quantification (2024) Vol. 12, Iss. 4, pp. 1165-1191
Open Access | Times Cited: 8
Uncertainty quantification for noisy inputs–outputs in physics-informed neural networks and neural operators
Zongren Zou, Xuhui Meng, George Em Karniadakis
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 433, pp. 117479-117479
Closed Access | Times Cited: 8
A Comprehensive and Fair Comparison between Mlp and Kan Representations for Differential Equations and Operator Networks
Khemraj Shukla, Juan Diego Toscano, Zhi-Cheng Wang, et al.
(2024)
Open Access | Times Cited: 6
A generative modeling framework for inferring families of biomechanical constitutive laws in data-sparse regimes
Minglang Yin, Zongren Zou, Enrui Zhang, et al.
Journal of the Mechanics and Physics of Solids (2023) Vol. 181, pp. 105424-105424
Open Access | Times Cited: 15
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements
Khemraj Shukla, Zongren Zou, Chi Hin Chan, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 433, pp. 117498-117498
Closed Access | Times Cited: 5
Role of Data-driven Regional Growth Model in Shaping Brain Folding Patterns
Jixin Hou, Zhengwang Wu, Xianyan Chen, et al.
Soft Matter (2025)
Open Access
Integrating neural operators with diffusion models improves spectral representation in turbulence modelling
Vivek Oommen, Aniruddha Bora, Zhen Zhang, et al.
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2025) Vol. 481, Iss. 2309
Closed Access
Uncertainty Quantification for Noisy Inputs-Outputs in Physics-Informed Neural Networks and Neural Operators
Zongren Zou, Xuhui Meng, George Em Karniadakis
(2024)
Open Access | Times Cited: 4
Synergistic learning with multi-task DeepONet for efficient PDE problem solving
Varun Kumar, Somdatta Goswami, Katiana Kontolati, et al.
Neural Networks (2025) Vol. 184, pp. 107113-107113
Closed Access
Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification
Zongren Zou, George Em Karniadakis
Journal of Computational Physics (2025), pp. 113947-113947
Closed Access
A novel machine learning method for real-time dynamic analysis of tensegrity flexible multibody systems
Ningning Song, Mingji Wang, Xinwei Wang, et al.
Nonlinear Dynamics (2025)
Closed Access
Large Scale Scattering Using Fast Solvers Based on Neural Operators
Zongren Zou, Adar Kahana, Enrui Zhang, et al.
(2024)
Open Access | Times Cited: 3
Automated Data-Driven Discovery of Material Models Based on Symbolic Regression: A Case Study on the Human Brain Cortex
Jixin Hou, Xianyan Chen, Taotao Wu, et al.
Acta Biomaterialia (2024)
Closed Access | Times Cited: 3
An augmented physics informed neural network approach for blunt-body dynamics
Shafi Al Salman Romeo, Furkan Oz, Ashraf Kassem, et al.
Physics of Fluids (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 2
Numerical investigation of nonlinear extended Fisher-Kolmogorov equation via quintic trigonometric B-spline collocation technique
Shafeeq Rahman Thottoli, Mohammad Tamsir, Mutum Zico Meetei, et al.
AIMS Mathematics (2024) Vol. 9, Iss. 7, pp. 17339-17358
Open Access | Times Cited: 1
A data-physic driven method for gear fault diagnosis using PINN and pseudo-dynamic features
Yikun Yang, Xifeng Wang, Jinfeng Li, et al.
Measurement (2024) Vol. 236, pp. 115124-115124
Closed Access | Times Cited: 1
Physics-specialized neural network with hard constraints for solving multi-material diffusion problems
Yuchen Xie, Honghang Chi, Yahui Wang, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 430, pp. 117223-117223
Closed Access | Times Cited: 1
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