Estimation and Uncertainties of Profiles and Equilibria for Fusion Modeling Codes
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 879-893
Technical Paper / dx.doi.org/10.1080/15361055.2020.1820794
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 894-900
Technical Paper / dx.doi.org/10.1080/15361055.2020.1819751
Deep Learning for the Analysis of Disruption Precursors Based on Plasma Tomography
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 901-911
Technical Paper / dx.doi.org/10.1080/15361055.2020.1820749
Progress Toward Interpretable Machine Learning–Based Disruption Predictors Across Tokamaks
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 912-924
Technical Paper / dx.doi.org/10.1080/15361055.2020.1798589
Automatic Recognition of Anomalous Patterns in Discharges by Applying Deep Learning
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 925-932
Technical Paper / dx.doi.org/10.1080/15361055.2020.1820804
Tools for Image Analysis and First Wall Protection at W7-X
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 933-941
Technical Paper / dx.doi.org/10.1080/15361055.2020.1819750
Cross Comparisons of X-Ray Imaging Crystal Spectrometer and Charge Exchange Spectroscopy from KSTAR
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 942-946
Technical Paper / dx.doi.org/10.1080/15361055.2020.1817705
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 947-956
Technical Paper / dx.doi.org/10.1080/15361055.2020.1820748
Position-Sensitive Detector in Neutron Tomography and Material Characterization
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 957-961
Technical Paper / dx.doi.org/10.1080/15361055.2020.1819749
Detection of Alfvén Eigenmodes on COMPASS with Generative Neural Networks
Fusion Science and Technology / Volume 76 / Number 8 / November 2020 / Pages 962-971
Technical Paper / dx.doi.org/10.1080/15361055.2020.1820805