Variational methods for machine learning with applications to deep networks

Variational methods for machine learning with applications to deep networks

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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 i...

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Bibliographic Details
Main Author: Cinelli, Lucas Pinheiro
Other Authors: Barros da Silva, Eduardo Antônio, Marins, Matheus Araújo, Netto, Sergio L (Sergio Lima), 1967-
Format: Electronic Book
Language:English
Published: Cham : Springer, 2021
Subjects:
Bayesian statistical decision theory
Machine learning
Neural networks (Computer science)
Neural Networks, Computer
Apprentissage automatique
Réseaux neuronaux (Informatique)
Théorie de la décision bayésienne

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