Trustworthy Artificial Intelligence for environmental sciences: An innovative approach for summer school
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Related Links |
Related Preprint #1 : Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI Related Preprint #2 : The AI Index 2022 Annual Report Related Software #1 : ai2es/tai4es-trustathon-2022: Trustworthy Artificial Intelligence for Environmental Science (TAI4ES) Summer School 2022 |
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Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
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Resource Support Email | opensky@ucar.edu |
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Author |
McGovern, A. Gagne, David John Wirz, Christopher D. Ebert-Uphoff, I. |
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UCAR/NCAR - Library |
Publication Date | 2023-06-01T00:00:00 |
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geoscientificInformation |
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Metadata Date | 2025-07-11T15:17:37.013888 |
Metadata Record Identifier | edu.ucar.opensky::articles:26487 |
Metadata Language | eng; USA |
Suggested Citation | McGovern, A., Gagne, David John, Wirz, Christopher D., Ebert-Uphoff, I., Bostrom, A., Rao, Y., Schumacher, A., Flora, M., Chase, R., Mamalakis, A., McGraw, M., Lagerquist, R., Redmon, R. J., Peterson, Taysia. (2023). Trustworthy Artificial Intelligence for environmental sciences: An innovative approach for summer school. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7183bjn. Accessed 03 August 2025. |
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