https://github.com/yeonghyeon/cvae
Implementation of Convolutional Variational Auto-Encoder (CVAE)
https://github.com/yeonghyeon/cvae
convolutional-neural-networks generative-neural-network variational-autoencoder
Last synced: 3 months ago
JSON representation
Implementation of Convolutional Variational Auto-Encoder (CVAE)
- Host: GitHub
- URL: https://github.com/yeonghyeon/cvae
- Owner: YeongHyeon
- License: mit
- Created: 2019-09-03T07:35:12.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2019-10-14T08:11:36.000Z (over 5 years ago)
- Last Synced: 2025-01-08T19:11:25.842Z (4 months ago)
- Topics: convolutional-neural-networks, generative-neural-network, variational-autoencoder
- Language: Python
- Homepage:
- Size: 986 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Convolutional Variational Auto-Encoder (CVAE)
=====
Implementation of Convolutional Variational Auto-Encoder (CVAE)
## Architecture
Simplified VAE architecture.
## Graph in TensorBoard
Graph of CVAE.
## Results
Restoration result by CVAE.
Latent vector space, and reconstruction result of latent space walking.
## Environment
* Python 3.7.4
* Tensorflow 1.14.0
* Numpy 1.17.1
* Matplotlib 3.1.1
* Scikit Learn (sklearn) 0.21.3
## Reference
[1] Kingma, D. P., & Welling, M. (2013). Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114.
[2] Kullback Leibler divergence. Wikipedia