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Introduction to variational autoencoders - Jack Morris
| | vxlabs.com
Variational Autoencoder in PyTorch, commented and annotated. - vxlabs
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| | I have recently become fascinated with (Variational) Autoencoders and with PyTorch. Kevin Frans has a beautiful blog post online explaining variational autoencoders, with examples in TensorFlow and, importantly, with cat pictures. Jaan Altosaar's blog post takes an even deeper look at VAEs from both the deep learning perspective and the perspective of graphical models. Both of these posts, as well as Diederik Kingma's original 2014 paper Auto-Encoding Variational Bayes, are more than worth your time.
| | dustintran.com
MuProp: Unbiased Backpropagation for Stochastic Neural Networks | Dustin Tran
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| | Having recently finished some papers with Rajesh Ranganath and Dave Blei on variational models [1] [2], I'm now a bit free to catch up on my reading of recen...
| | www.nicktasios.nl
Latent Diffusion Series: Variational Autoencoder (VAE) | NICK TASIOS
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| | In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In the second post, we will bu
| | pyimagesearch.com
PyTorch: Training your first Convolutional Neural Network (CNN) - PyImageSearch
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| In this tutorial, you will receive a gentle introduction to training your first Convolutional Neural Network (CNN) using the PyTorch deep learning library.