Variational autoencoder architecture. Made with https://github.com/battlesnake/neural.
Edit and compile if you like:
% Variational autoencoder architecture.% Made with https://github.com/battlesnake/neural.\documentclass[tikz]{standalone}\usepackage{neuralnetwork}\newcommand{\xin}[2]{$x_#2$}\newcommand{\xout}[2]{$\hat x_#2$}\begin{document}\begin{neuralnetwork}[height=8]\tikzstyle{input neuron}=[neuron, fill=orange!70];\tikzstyle{output neuron}=[neuron, fill=blue!60!black, text=white];\inputlayer[count=8, bias=false, title=Input Layer, text=\xin]\hiddenlayer[count=5, bias=false]\linklayers\hiddenlayer[count=3, bias=false, title=Latent\\Representation]\linklayers\hiddenlayer[count=5, bias=false]\linklayers\outputlayer[count=8, title=Output Layer, text=\xout]\linklayers\end{neuralnetwork}\end{document}
Click to download: autoencoder.tex
Open in Overleaf: autoencoder.tex
This file is available on tikz.netlify.app and on GitHub and is MIT licensed.
See more on the author page of Janosh Riebesell..