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..