46 citations · 69 across the 4 of their papers we have counts for
5 papers
Automatic classification of plasma regions in near-Earth space with supervised machine learning: application to Magnetospheric Multi Scale 2016-2019 observations
Hugo Breuillard, Romain Dupuis, Alessandro Retino +3
The proper classification of plasma regions in near-Earth space is crucial to perform unambiguous statistical studies of fundamental plasma processes such as shocks, magnetic recon…
Tokamak disruption prediction using different machine learning techniques
Joost Croonen, Jorge Amaya, Giovanni Lapenta
Disruption prediction and mitigation is of key importance in the development of sustainable tokamakreactors. Machine learning has become a key tool in this endeavour. In this paper…
Visualizing and Interpreting Unsupervised Solar Wind Classifications
Jorge Amaya, Romain Dupuis, Maria Elena Innocenti +1
One of the goals of machine learning is to eliminate tedious and arduous repetitive work. The manual and semi-automatic classification of millions of hours of solar wind data from…
Characterizing magnetic reconnection regions using Gaussian mixture models on particle velocity distributions
Romain Dupuis, Martin V. Goldman, David L. Newman +2
We present a method based on unsupervised machine learning to identify regions of interest using particle velocity distributions as a signature pattern. An automatic density estima…
Application performance on a Cluster-Booster system
Anke Kreuzer, Jorge Amaya, Norbert Eicker +1
The DEEP projects have developed a variety of hardware and software technologies aiming at improving the efficiency and usability of next generation high-performance computers. The…