https://github.com/xnought/vae-explainer
Interactive Variational Autoencoder (VAE)
https://github.com/xnought/vae-explainer
keras ml tfjs
Last synced: 12 days ago
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Interactive Variational Autoencoder (VAE)
- Host: GitHub
- URL: https://github.com/xnought/vae-explainer
- Owner: xnought
- License: mit
- Created: 2024-08-31T14:04:16.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-10-26T23:04:45.000Z (6 months ago)
- Last Synced: 2025-03-24T11:56:49.529Z (29 days ago)
- Topics: keras, ml, tfjs
- Language: Jupyter Notebook
- Homepage: https://xnought.github.io/vae-explainer/
- Size: 16.5 MB
- Stars: 47
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
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/
https://github.com/user-attachments/assets/ef788f0a-9c66-48fb-99d9-f4feb62ca9cd
## Development
```bash
pnpm install
pnpm dev
```
which runs the hot-reloading dev server at http://localhost:5173
## Cite
```bibtex
@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},
}
```
## Code References
- 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/