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https://github.com/Schlumberger/joint-vae
Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:
https://github.com/Schlumberger/joint-vae
disentangled-representations disentanglement generative-models gumbel-softmax pytorch vae
Last synced: about 2 months ago
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Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:
- Host: GitHub
- URL: https://github.com/Schlumberger/joint-vae
- Owner: Schlumberger
- License: mit
- Created: 2018-05-08T01:48:14.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-04-02T01:46:48.000Z (about 5 years ago)
- Last Synced: 2024-01-26T18:36:17.994Z (4 months ago)
- Topics: disentangled-representations, disentanglement, generative-models, gumbel-softmax, pytorch, vae
- Language: Jupyter Notebook
- Homepage:
- Size: 34.5 MB
- Stars: 455
- Watchers: 21
- Forks: 64
- Open Issues: 1
Lists
- Awesome-pytorch-list - joint-vae
- Awesome-pytorch-list-CNVersion - joint-vae
- my-awesome-stars - Schlumberger/joint-vae - Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2: (Jupyter Notebook)