Learn how Variational Autoencoders (VAE) work by visualizing one running in your browser.
- Live Site: https://xnought.github.io/vae-explainer/
- Paper: https://arxiv.org/abs/2409.09011
- Also interetested in VQ-VAEs? Check out https://xnought.github.io/vq-vae-explainer/
demo.mov
pnpm install pnpm dev
which runs the hot-reloading dev server at http://localhost:5173
@misc{bertucci2024vaeexplainer, title={VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization}, author={Donald Bertucci and Alex Endert}, year={2024}, eprint={2409.09011}, archivePrefix={arXiv}, primaryClass={cs.HC}, url={https://arxiv.org/abs/2409.09011}, }
- https://keras.io/examples/generative/vae/
- https://www.ibm.com/think/topics/variational-autoencoder#:~:text=Variational%20autoencoders%20(VAEs)%20are%20generative,other%20autoencoders%2C%20such%20as%20denoising.
- https://www.youtube.com/watch?v=9zKuYvjFFS8
- https://arxiv.org/abs/1312.6114 (original VAE paper)
- https://www.youtube.com/watch?v=afNuE5z2CQ8
- https://keras.io/examples/keras_recipes/trainer_pattern/