135 citations · 1.3k across the 86 of their papers we have counts for
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astro-ph.IM2019★ 7 cited
Studying deep convolutional neural networks with hexagonal lattices for imaging atmospheric Cherenkov telescope event reconstruction
D. Nieto, A. Brill, Q. Feng +4
Deep convolutional neural networks (DCNs) are a promising machine learning technique to reconstruct events recorded by imaging atmospheric Cherenkov telescopes (IACTs), but require…
astro-ph.IM2019★ 5 cited
CTLearn: Deep Learning for Gamma-ray Astronomy
D. Nieto, A. Brill, Q. Feng +5
CTLearn is a new Python package under development that uses the deep learning technique to analyze data from imaging atmospheric Cherenkov telescope (IACT) arrays. IACTs use the Ch…