Machine learning surrogates of Bayesian models of nuclear fusion experiments

Pavone, A.; W7-X Team, Max Planck Institute for Plasma Physics, Max Planck Society

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Machine learning surrogates of Bayesian models of nuclear fusion experiments

Pavone, A., & W7-X Team, Max Planck Institute for Plasma Physics, Max Planck Society (2021). Machine learning surrogates of Bayesian models of nuclear fusion experiments. Talk presented at 63rd Annual Meeting of the APS Division of Plasma Physics. Pittsburgh, PA. 2021-11-08 - 2021-11-12.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-A627-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-A628-F

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Creators:
Pavone, A.¹, Author
W7-X Team, Max Planck Institute for Plasma Physics, Max Planck Society, Author

Affiliations:
1Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society, ou_2040305

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Language(s): eng - English

Dates: Submitted: 2021

Publication Status: Submitted

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Title: 63rd Annual Meeting of the APS Division of Plasma Physics

Place of Event: Pittsburgh, PA

Start-/End Date: 2021-11-08 - 2021-11-12

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