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Автор: Pinheiro Cinelli, L., Marins, M.A., Barros da Silva, E.A., Silva, P.S.L.e.
Издательство: Springer
Год: 2021
Формат: true pdf/epub
Страниц: 173
Размер: 15.8 Mb
Язык: English
This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models. Starting from the model-based approach to Machine Learning, the authors motivate Probabilistic Graphical Models and show how Bayesian inference naturally lends itself to this framework. The authors present detailed explanations of the main modern algorithms on variational approximations for Bayesian inference in neural networks.