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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:

Bayesian Graph Convolutional Neural Networks via Tempered MCMC
Rohitash Chandra, Ayush Bhagat, Manavendra Maharana, et al.
IEEE Access (2021) Vol. 9, pp. 130353-130365
Open Access | Times Cited: 21

Showing 21 citing articles:

A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
Expert Systems with Applications (2023) Vol. 244, pp. 122778-122778
Open Access | Times Cited: 134
COVID-19 sentiment analysis via deep learning during the rise of novel cases
Rohitash Chandra, Aswin Krishna
PLoS ONE (2021) Vol. 16, Iss. 8, pp. e0255615-e0255615
Open Access | Times Cited: 114
SMOTified-GAN for Class Imbalanced Pattern Classification Problems
Anurag Sharma, Prabhat Kumar Singh, Rohitash Chandra
IEEE Access (2022) Vol. 10, pp. 30655-30665
Open Access | Times Cited: 73
A Review on Bayesian Deep Learning in Healthcare: Applications and Challenges
Abdullah A. Abdullah, Masoud Muhammed Hassan, Yaseen T. Mustafa
IEEE Access (2022) Vol. 10, pp. 36538-36562
Open Access | Times Cited: 68
A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications
Xinlei Zhou, Han Liu, Farhad Pourpanah, et al.
Neurocomputing (2021) Vol. 489, pp. 449-465
Open Access | Times Cited: 50
Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic
Rohitash Chandra, Yixuan He
PLoS ONE (2021) Vol. 16, Iss. 7, pp. e0253217-e0253217
Open Access | Times Cited: 47
Bayesian Neural Networks via MCMC: A Python-Based Tutorial
Rohitash Chandra, Joshua A. Simmons
IEEE Access (2024) Vol. 12, pp. 70519-70549
Open Access | Times Cited: 7
Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks
Arpit Kapoor, Anshul Negi, Lucy Marshall, et al.
Environmental Modelling & Software (2023) Vol. 162, pp. 105654-105654
Open Access | Times Cited: 14
Revisiting Bayesian Autoencoders With MCMC
Rohitash Chandra, Mahir Jain, Manavendra Maharana, et al.
IEEE Access (2022) Vol. 10, pp. 40482-40495
Open Access | Times Cited: 20
Structural safety evaluation using Bayesian ensemble neural networks
Jin-Ling Zheng, Sheng-En Fang
Engineering Structures (2025) Vol. 328, pp. 119709-119709
Closed Access
A Systematic Survey of Graph Convolutional Networks for Artificial Intelligence Applications
Amutha Sadasivan, Kavipriya Gananathan, Joe Dhanith Pal Nesamony Rose Mary, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2025) Vol. 15, Iss. 2
Closed Access
Gradient boosting Bayesian neural networks via Langevin MCMC
George Bai, Rohitash Chandra
Neurocomputing (2023) Vol. 558, pp. 126726-126726
Open Access | Times Cited: 7
Bayesian neuroevolution using distributed swarm optimization and tempered MCMC
Arpit Kapoor, Eshwar Nukala, Rohitash Chandra
Applied Soft Computing (2022) Vol. 129, pp. 109528-109528
Closed Access | Times Cited: 8
Hierarchical Graph Neural Network Based on Semi-Implicit Variational Inference
Hailong Su, Zhipeng Li, Xiaobo Zhu, et al.
IEEE Transactions on Cognitive and Developmental Systems (2022) Vol. 15, Iss. 2, pp. 887-895
Open Access | Times Cited: 7
Sequential reversible jump MCMC for dynamic Bayesian neural networks
Nhat-Minh Nguyen, Minh‐Ngoc Tran, Rohitash Chandra
Neurocomputing (2023) Vol. 564, pp. 126960-126960
Open Access | Times Cited: 3
Bayesian neural networks via MCMC: a Python-based tutorial
Rohitash Chandra, Royce Chen, Joshua A. Simmons
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Variational graph neural network with diffusion prior for link prediction
Hailong Su, Zhipeng Li, Changan Yuan, et al.
Applied Intelligence (2024) Vol. 55, Iss. 2
Open Access
A Hierarchical Nonparametric Bayesian Model Based on Scaled Dirichlet Distribution
Narges Manouchehri, Ali Baghdadi, Nizar Bouguila
(2021), pp. 61-68
Closed Access | Times Cited: 1
Bayesian Networks based the working status judgment model for light buoys in the Shanwei Port area
Wenfeng Sun, Sheng Zhao, Bing Wu
(2023), pp. 2334-2340
Closed Access
Enhancing Image Classification with Bayesian Neural Networks: Improved Training Techniques and Decision Strategies for Reliable AI Support in Uncertainty-Sensitive Tasks
Yan.Cheng. Liu, Hua.Jun Huang, Yi.Wen Wang
(2023), pp. 332-336
Closed Access
COVID-19 sentiment analysis via deep learning during the rise of novel cases
Rohitash Chandra, Aswin Krishna
arXiv (Cornell University) (2021)
Closed Access
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