## 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.

** Published:**

This post is aimed at those who want to understand the mathematical framework of denoising diffusion probabilistic model and its implementation in deep learning.

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In this post I explain the mathematics behind conditional variational autoencoders and the differences with conventional variational autoencoders.

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This post is aimed at those who want to understand the mathematical framework of variational autoencoders and its implementation in deep learning.

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The aim of this post is to present the key stages/concepts of contrastive learning.

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Are you interested in understanding the mathematics that underlie the transformer? If so, this post is tailored for you!