Open AccessThe comparison of autoencoder architectures in improving of prediction models
Author(s) -
А. В. Просветов
Publication year - 2018
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1117/1/012006
Subject(s) - encode , computer science , autoencoder , encoding (memory) , artificial neural network , artificial intelligence , field (mathematics) , task (project management) , feature (linguistics) , machine learning , domain (mathematical analysis) , recurrent neural network , event (particle physics) , encoder , mathematical analysis , biochemistry , chemistry , linguistics , philosophy , mathematics , management , pure mathematics , economics , gene , physics , quantum mechanics , operating system