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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysisстатья
- Авторы: Chernoded Andrey, Dudko Lev, Myagkov Igor, Volkov Petr
- Журнал: EPJ Web of Conferences
- Том: 158
- Год издания: 2017
- DOI: 10.1051/epjconf/201715806008
- Аннотация: Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.
- Добавил в систему: Волков Петр Владимирович