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Alberto Guillen et al.
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Yajun Fan et al.
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A. Guillen et al.
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Francisco Carrillo-Perez et al.
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2019, PT I (2019)
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Filipe Assuncao et al.
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Shahab Shamshirband et al.
IEEE ACCESS (2019)
Graph Neural Networks for IceCube Signal Classification
Nicholas Choma et al.
2018 17TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA) (2018)
Combination of EEG Data Time and Frequency Representations in Deep Networks for Sleep Stage Classification
Marti Manzano et al.
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Marti Manzano et al.
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Gamma/hadron separation in HAWC using neural networks
T. Capistran et al.
GROUND-BASED AND AIRBORNE INSTRUMENTATION FOR ASTRONOMY VI (2016)
Design and performances of prototype muon detectors of LHAASO-KM2A
Xiong Zuo et al.
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT (2015)
Python for scientific computing
Travis E. Oliphant
COMPUTING IN SCIENCE & ENGINEERING (2007)
GEANT4-a simulation toolkit
S Agostinelli et al.
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Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)