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J. Amaya

8 papers hereh-index 14597 citations51 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author6

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.DC3
  • physics.plasm-ph3
  • astro-ph.SR1
  • physics.space-ph1
same name
  • J. Amaya — 2 papers, h 7
  • J. Amaya — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedAutomatic classification of plasma regions in near-Earth space with supervised machine learning: application to Magnetospheric Multi Scale 2016-2019 observations

46 citations · 75 across the 5 of their papers we have counts for

collaborators
Showing physics.plasm-phShow all

3 papers · 1 filter

physics.plasm-ph2020★ 46 cited

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…

physics.plasm-ph2020

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…

physics.plasm-ph2019★ 14 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.