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 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
Rohitash Chandra, Joshua A. Simmons
IEEE Access (2024) Vol. 12, pp. 70519-70549
Open Access | Times Cited: 7
Showing 7 citing articles:
Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels
Eric Chen, Martin S. Andersen, Rohitash Chandra
Environmental Modelling & Software (2024) Vol. 178, pp. 106072-106072
Closed Access | Times Cited: 7
Eric Chen, Martin S. Andersen, Rohitash Chandra
Environmental Modelling & Software (2024) Vol. 178, pp. 106072-106072
Closed Access | Times Cited: 7
Federated learning meets Bayesian neural network: Robust and uncertainty-aware distributed variational inference
Pengfei Li, Qinghua Hu, Xiaofei Wang
Neural Networks (2025) Vol. 185, pp. 107135-107135
Closed Access
Pengfei Li, Qinghua Hu, Xiaofei Wang
Neural Networks (2025) Vol. 185, pp. 107135-107135
Closed Access
Comparative assessment of sewer sampling methods for infectious disease surveillance: Insights from transport modeling and simulations of SARS-CoV-2 emissions
Min Jeong Ban, Keugtae Kim, Sungpyo Kim, et al.
Water Research (2025) Vol. 278, pp. 123373-123373
Closed Access
Min Jeong Ban, Keugtae Kim, Sungpyo Kim, et al.
Water Research (2025) Vol. 278, pp. 123373-123373
Closed Access
Mixed Student’s T-Distribution Regression Soft Measurement Model and Its Application Based on VI and MCMC
Qirui Li, C. C. Li, Zhiping Peng, et al.
Processes (2025) Vol. 13, Iss. 3, pp. 861-861
Open Access
Qirui Li, C. C. Li, Zhiping Peng, et al.
Processes (2025) Vol. 13, Iss. 3, pp. 861-861
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
Ehsan Farahbakhsh, Dakshi Goel, Dhiraj Pimparkar, et al.
PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science (2025)
Open Access
Gaussian mixture models for training Bayesian convolutional neural networks
Bakhouya Mostafa, Hassan Ramchoun, Hadda Mohammed, et al.
Evolutionary Intelligence (2024) Vol. 17, Iss. 4, pp. 2515-2536
Closed Access | Times Cited: 3
Bakhouya Mostafa, Hassan Ramchoun, Hadda Mohammed, et al.
Evolutionary Intelligence (2024) Vol. 17, Iss. 4, pp. 2515-2536
Closed Access | Times Cited: 3
Data-Driven autonomous printing process optimization and real-time abnormality identification in aerosol jet-deposited droplet morphology
Haining Zhang, Lin Cui, Pil-Ho Lee, et al.
Virtual and Physical Prototyping (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 2
Haining Zhang, Lin Cui, Pil-Ho Lee, et al.
Virtual and Physical Prototyping (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 2
Hierarchical Meta-learning-based Adaptive Controller
Fengze Xie, Guanya Shi, Michael O’Connell, et al.
(2024), pp. 18309-10315
Open Access | Times Cited: 1
Fengze Xie, Guanya Shi, Michael O’Connell, et al.
(2024), pp. 18309-10315
Open Access | Times Cited: 1
