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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:

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

Showing 20 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
Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection
Bang Xiang Yong, Alexandra Brintrup
Expert Systems with Applications (2022) Vol. 209, pp. 118196-118196
Open Access | Times Cited: 31
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
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants
Liyao Gao, J. Nathan Kutz
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2024) Vol. 480, Iss. 2286
Open Access | Times Cited: 4
Towards trustworthy cybersecurity operations using Bayesian Deep Learning to improve uncertainty quantification of anomaly detection
Tengfei Yang, Yuansong Qiao, Brian Lee
Computers & Security (2024) Vol. 144, pp. 103909-103909
Open Access | Times Cited: 4
A clustering and graph deep learning-based framework for COVID-19 drug repurposing
Chaarvi Bansal, Perinkulam Ravi Deepa, Vinti Agarwal, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123560-123560
Open Access | Times Cited: 4
Multi-modal deep learning for credit rating prediction using text and numerical data streams
Mahsa Tavakoli, Rohitash Chandra, Fengrui Tian, et al.
Applied Soft Computing (2025), pp. 112771-112771
Open Access
Convolutional Neural Networks for Mineral Prospecting Through Alteration Mapping with Remote Sensing Data
Ehsan Farahbakhsh, Dakshi Goel, Dhiraj Pimparkar, et al.
PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science (2025)
Open 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
Software reliability prediction: A machine learning and approximation Bayesian inference approach
Shahrzad Oveisi, Ali Moeini, Sayeh Mirzaei, et al.
Quality and Reliability Engineering International (2024) Vol. 40, Iss. 7, pp. 4004-4037
Open Access | Times Cited: 1
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
Evolutionary computation-based reliability quantification and its application in big data analysis on semiconductor manufacturing
Qiao Xu, Naigong Yu, Mohammad Mehedi Hasan
Applied Soft Computing (2023) Vol. 136, pp. 110080-110080
Closed Access | Times Cited: 2
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
To follow or not to follow - Estimating political opinion from Twitter data using a network-based machine learning approach
Nils Brandenstein, Christian Montag, Cornelia Sindermann
(2024)
Open Access
Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) Framework
Jesse Stevens, Daniël N. Wilke, Isaac I. Setshedi
Mathematical and Computational Applications (2024) Vol. 29, Iss. 5, pp. 85-85
Open Access
Towards Trustworthy Cybersecurity Operations Using Bayesian Deep Learning to Improve Uncertainty Quantification of Anomaly Detection
Tengfei Yang, Yuansong Qiao, Brian Lee
(2023)
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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