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GammaLearn

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 27 Mar 2023 English Publisher:ZenodoFunded by:EC | ESCAPE
Authors: Jacquemont, Mikael; Vuillaume, Thomas; Dell'aiera, Michaël; Vuillaume, Thomas; Trivellato, Thomas;

doi: 10.5281/zenodo.7774265 , 10.5281/zenodo.7991254

Abstract

Release Notes: GammaLearn v10.0 introduces new domain adaptation techniques with DeepJDot and DeepCoral. The data loading of the vision datasets has been refactored to make it more general. The containerization is improved with an environment layer using mamba. The documentation has been improved.

GammaLearn is a collaborative project to apply deep learning to the analysis of low-level Imaging Atmospheric Cherenkov Telescopes such as CTA. It provides a framework to easily train and apply models from a configuration file. Learn more at https://purl.org/gammalearn

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Keywords

machine learning, cta, Gamma-ray telescopes, deep learning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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