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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:

VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification
Shailesh Garg, Souvik Chakraborty
Engineering Applications of Artificial Intelligence (2022) Vol. 118, pp. 105685-105685
Closed Access | Times Cited: 18

Showing 18 citing articles:

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: 41
DeepOKAN: Deep operator network based on Kolmogorov Arnold networks for mechanics problems
Diab W. Abueidda, Panos Pantidis, Mostafa E. Mobasher
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 436, pp. 117699-117699
Open Access | Times Cited: 7
A multi-fidelity deep operator network (DeepONet) for fusing simulation and monitoring data: Application to real-time settlement prediction during tunnel construction
Xu Chen, Ba Trung Cao, Yong Yuan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108156-108156
Open Access | Times Cited: 11
En-DeepONet: An enrichment approach for enhancing the expressivity of neural operators with applications to seismology
Ehsan Haghighat, Umair bin Waheed, George Em Karniadakis
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 420, pp. 116681-116681
Closed Access | Times Cited: 15
Conformalized-DeepONet: A distribution-free framework for uncertainty quantification in deep operator networks
Christian Moya, Amirhossein Mollaali, Zecheng Zhang, et al.
Physica D Nonlinear Phenomena (2024), pp. 134418-134418
Closed Access | Times Cited: 5
A survey on machine learning approaches for uncertainty quantification of engineering systems
Yan Shi, Pengfei Wei, Ke Feng, et al.
Machine learning for computational science and engineering (2025) Vol. 1, Iss. 1
Open Access
MAntRA: A framework for model agnostic reliability analysis
Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, et al.
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109233-109233
Open Access | Times Cited: 10
Bayesian deep neural networks for spatio-temporal probabilistic optimal power flow with multi-source renewable energy
Fang Gao, Zidong Xu, Linfei Yin
Applied Energy (2023) Vol. 353, pp. 122106-122106
Closed Access | Times Cited: 10
Nonparametric formulation of polynomial chaos expansion based on least-square support-vector machines
Paolo Manfredi, Riccardo Trinchero
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108182-108182
Open Access | Times Cited: 3
MODNO: Multi-Operator learning with Distributed Neural Operators
Zecheng Zhang
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 431, pp. 117229-117229
Open Access | Times Cited: 1
Multi-fidelity wavelet neural operator surrogate model for time-independent and time-dependent reliability analysis
Tapas Tripura, Akshay Thakur, Souvik Chakraborty
Probabilistic Engineering Mechanics (2024) Vol. 77, pp. 103672-103672
Closed Access | Times Cited: 1
Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations
Sawan Kumar, Rajdip Nayek, Souvik Chakraborty
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 431, pp. 117265-117265
Open Access | Times Cited: 1
Learning latent space dynamics with model-form uncertainties: A stochastic reduced-order modeling approach
Jin Yi Yong, Rudy Geelen, Johann Guilleminot
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 435, pp. 117638-117638
Closed Access | Times Cited: 1
Physics informed WNO
N. Navaneeth, Tapas Tripura, Souvik Chakraborty
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 418, pp. 116546-116546
Closed Access | Times Cited: 3
Fuzzy Granular Computing for Evaluating Average Uncertainty in Machine Learning Models
Naimeh Sadeghi, Nima Gerami Seresht, Witold Pedrycz, et al.
(2024)
Closed Access
Fast Solving Partial Differential Equations via Imitative Fourier Neural Operator
Lulu Cao, Haokai Hong, Min Jiang
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 76, pp. 1-8
Closed Access
uncertainty quantification for DeepONets with Ensemble Kalman Inversion
Andrew Pensoneault, Xueyu Zhu
Journal of Computational Physics (2024), pp. 113670-113670
Closed Access
Sim‐Net: Simulation Net for Solving Seepage Equation Under Unsteady Boundary
Daolun Li, Enyuan Chen, Yantao Xu, et al.
International Journal for Numerical Methods in Fluids (2024)
Closed Access
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