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CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 18 Mar 2018 English Publisher:ZenodoFunded by:EC | ESCAPE
Authors: Brill, Ari; Kim, Bryan; Nieto, Daniel; Miener, Tjark; Feng, Qi;

doi: 10.5281/zenodo.6842323 , 10.5281/zenodo.7908252 , 10.5281/zenodo.3342952 , 10.5281/zenodo.11475531 , 10.5281/zenodo.15021424 , 10.5281/zenodo.4576196 , 10.5281/zenodo.12742579 , 10.5281/zenodo.5772815 , 10.5281/zenodo.3342954 , 10.5281/zenodo.3345947 , 10.5281/zenodo.15065761 , 10.5281/zenodo.15065535 , 10.5281/zenodo.5947837

CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction

Abstract

CTLearn is a high-level Python package providing a backend for training deep learning models for the reconstruction of imaging atmospheric Cherenkov telescope events using TensorFlow.

Related Organizations
Keywords

Event reconstruction, Deep learning, High energy physics, Imaging atmospheric Cherenkov telescopes

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citations
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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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2
Average
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27
2
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