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Dynamical Variational Autoencoders: A Comprehensive Review - Foundations and Trends® in Machine Learning
Laurent Girin
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Dynamical Variational Autoencoders: A Comprehensive Review - Foundations and Trends® in Machine Learning
Laurent Girin
Variational autoencoders are powerful deep generative models widely used to represent high-dimensional complex data through a low-dimensional latent space learned in an unsupervised manner. In this volume, the authors introduce and discuss a general class of models, called dynamical variational autoencoders.
198 pages
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | December 2, 2021 |
| ISBN13 | 9781680839128 |
| Publishers | now publishers Inc |
| Pages | 198 |
| Dimensions | 156 × 234 × 10 mm · 286 g |
| Language | English |
See all of Laurent Girin ( e.g. Paperback Book )