Neural network surrogates of Bayesian diagnostic models for fast inference of plasma parameters-Reference-Cited by-同舟云学术

Neural network surrogates of Bayesian diagnostic models for fast inference of plasma parameters

Published:2021-03-01 Issue:3 Volume:92 Page:033531
ISSN:0034-6748
Container-title:Review of Scientific Instruments
language:en
Short-container-title:Review of Scientific Instruments

Author:

Pavone A.¹^ORCID,Svensson J.¹,Krychowiak M.¹,Hergenhahn U.¹^ORCID,Winters V.¹^ORCID,Kornejew P.¹,Kwak S.¹^ORCID,Hoefel U.¹^ORCID,Koenig R.¹^ORCID,Wolf R. C.¹^ORCID,

Affiliation:

1. Max-Planck-Institute for Plasma Physics, Greifswald 17491, Germany

Funder

H2020 Euratom

Publisher

AIP Publishing

Subject

Instrumentation

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0043772

Reference24 articles.

1. Bayesian modelling of the emission spectrum of the Joint European Torus Lithium Beam Emission Spectroscopy system

2. Bayesian electron density inference from JET lithium beam emission spectra using Gaussian processes

3. Bayesian modeling of microwave radiometer calibration on the example of the Wendelstein 7-X electron cyclotron emission diagnostic

4. Forward Modeling of X-Ray Imaging Crystal Spectrometers Within the Minerva Bayesian Analysis Framework

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