Dr Joyjit Chatterjee J.Chatterjee@hull.ac.uk
Visiting Academic
Artificial intelligence (AI) can help facilitate wider adoption of renewable energy globally. We organized a social event for the AI and renewables community to discuss these aspects at the International Conference on Learning Representations (ICLR), a leading AI conference. This opinion reflects on the key messages and provides a call for action on leveraging AI for transition toward net zero.
Chatterjee, J., & Dethlefs, N. (2022). Facilitating a smoother transition to renewable energy with AI. Patterns, 3(6), Article 100528. https://doi.org/10.1016/j.patter.2022.100528
Acceptance Date | May 11, 2022 |
---|---|
Publication Date | Jun 10, 2022 |
Deposit Date | Jul 11, 2022 |
Publicly Available Date | Jul 12, 2022 |
Journal | Patterns |
Electronic ISSN | 2666-3899 |
Publisher | Cell Press |
Peer Reviewed | Peer Reviewed |
Volume | 3 |
Issue | 6 |
Article Number | 100528 |
DOI | https://doi.org/10.1016/j.patter.2022.100528 |
Public URL | https://hull-repository.worktribe.com/output/4015610 |
Ensure access to affordable, reliable, sustainable and modern energy for all
Published article
(253 Kb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0
Copyright Statement
© 2022 The Author(s)
Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines
(2020)
Journal Article
Natural Language Generation for Operations and Maintenance in Wind Turbines
(2019)
Presentation / Conference Contribution
About Repository@Hull
Administrator e-mail: repository@hull.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search