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

Matos, F.; Svensson, J.; Pavone, A.; Odstrcil, T.; Jenko, F.

doi:10.1063/5.0020680

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Journal Article

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

MPS-Authors

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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;

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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;

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https://doi.org/10.1063/5.0020680
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Matos_Deep.pdf
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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

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