Variational methods for machine learning with applications to deep networks
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...
| Main Author: | Cinelli, Lucas Pinheiro. |
|---|---|
| Other Authors: | Marins, Matheus Araújo., Barros da Silva, Eduardo Antônio., Netto, Sergio L. 1967-, SpringerLink (Online service) |
| Format: | Electronic |
| Language: | English |
| Published: |
Cham :
Springer,
2021.
Cham : 2021. |
| Physical Description: |
1 online resource (173 pages) |
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |