Olivier Bernard
Professor at the university of Lyon (INSA), France and deputy director of the CREATIS laboratory
- Lyon, France
- Github
- Google Scholar
- ORCID
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The denoising diffusion probabilistic models (DDPM) paradigm demystified
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This post is aimed at those who want to understand the mathematical framework of denoising diffusion probabilistic model and its implementation in deep learning.
What about the conditional variational autoencoder?
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In this post I explain the mathematics behind conditional variational autoencoders and the differences with conventional variational autoencoders.
The variational autoencoder paradigm demystified
less than 10 minute read
Published:
This post is aimed at those who want to understand the mathematical framework of variational autoencoders and its implementation in deep learning.
The beauty of contrastive learning: a new step toward efficient unsupervised learning
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Published:
The aim of this post is to present the key stages/concepts of contrastive learning.