English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Deep learning for Gaussian process soft x-ray tomography model selection in the ASDEX Upgrade tokamak

MPS-Authors
/persons/resource/persons217480

Matos,  F.
Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society;

/persons/resource/persons110611

Svensson,  J.
Stellarator Dynamics and Transport (E5), Max Planck Institute for Plasma Physics, Max Planck Society;

/persons/resource/persons203816

Pavone,  A.
Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society;

/persons/resource/persons109509

Jenko,  F.
Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society;

External Resource

https://doi.org/10.1063/5.0020680
(Publisher version)

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

Matos_Deep.pdf
(Any fulltext), 608KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Matos, F., Svensson, J., Pavone, A., Odstrcil, T., & Jenko, F. (2020). Deep learning for Gaussian process soft x-ray tomography model selection in the ASDEX Upgrade tokamak. Review of Scientific Instruments, 91: 103501. doi:10.1063/5.0020680.


Cite as: https://hdl.handle.net/21.11116/0000-0007-43D3-F
Abstract
There is no abstract available