Understanding Variational Autoencoders (VAEs) | by Joseph Rocca | Towards Data Science

Building, step by step, the reasoning that leads to VAEs.

Difference between AutoEncoder (AE) and Variational AutoEncoder (VAE) | Towards Data Science Difference between AutoEncoder (AE) and Variational AutoEncoder (VAE) How can you compress data or even generate data from random values? That is what Autoencoder and Variational Autoencoder are. Aqeel Anwar Nov 3, 2021 9 min read Share The ability to simplify means to eliminate the unnecessary so that the necessary may speak — Hans Hofmann Context— Data compression Data compression is an essential phase in training a network. The idea is to compress the data so that the same amount of information can

saved by

• Claire Wang
• Emma Guo
• Asher P
• Lydia Nottingham
• Zhi Zhang
• Jacob G-W
• Vihaan Sondhi
• Timothy Kostolansky

related reading

• Variational autoencoders.jeremyjordan.me
• Tutorial - What is a variational autoencoder? – Jaan Lı 李jaan.io
• Variational AutoEncoders (VAE) with PyTorch - Alexander Van de Kleutavandekleut.github.io
• Tutorial on Variational Autoencodersarxiv.org
• Variational autoencoder - Wikipediaen.wikipedia.org
• Understanding VQ-VAE (DALL-E Explained Pt. 1)mlberkeley.substack.com
• From Autoencoder to Beta-VAE | Lil'Loglilianweng.github.io
• Generative modelling in latent space – Sander Dielemansander.ai
• Jupyter Notebook Viewernbviewer.org
• [1906.02691] An Introduction to Variational Autoencodersarxiv.org
• Autoencoder - Wikipediaen.wikipedia.org
• An Intuitive Explanation of Sparse Autoencoders for LLM Interpretability | Adam Karvonenadamkarvonen.github.io