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  Classification of tokamak plasma confinement states with convolutional recurrent neural networks

Matos, F., Menkovski, V., Felici, F., Pau, A., Jenko, F., TCV Team, et al. (2020). Classification of tokamak plasma confinement states with convolutional recurrent neural networks. Talk presented at DPG-Frühjahrstagung der Sektion Atome, Moleküle, Quantenoptik und Plasmen (SAMOP). Hannover. 2020-03-08 - 2020-03-13.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-BD02-4 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-BD03-3
Genre: Talk

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 Creators:
Matos, F.1, Author           
Menkovski, V.2, Author
Felici, F.2, Author
Pau, A.2, Author
Jenko, F.1, Author           
TCV Team, Author              
EUROfusion MST1 Team, Author              
Affiliations:
1Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856309              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2019
 Publication Status: Submitted
 Pages: -
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 Rev. Type: -
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Title: DPG-Frühjahrstagung der Sektion Atome, Moleküle, Quantenoptik und Plasmen (SAMOP)
Place of Event: Hannover
Start-/End Date: 2020-03-08 - 2020-03-13

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Title: Verhandlungen der Deutschen Physikalischen Gesellschaft
  Other : Verhandl. DPG
Source Genre: Journal
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Publ. Info: Bad Honnef : DPG
Pages: - Volume / Issue: (VI) 55 (1) Sequence Number: P 21.4 Start / End Page: - Identifier: CoNE: https://pure.mpg.de/cone/journals/resource/04200195
ISSN: 0420-0195