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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
| Date | Stars |
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| 2026-07-24 | 592 |
| 2026-07-25 | 592 |
| 2026-07-28 | 592 |
| 2026-07-30 | 592 |
| 2026-07-31 | 592 |
| 2026-08-06 | 592 |
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# TF-VAE-GAN-DRAW TensorFlow implementation of [Deep Convolutional Generative Adversarial Networks](http://arxiv.org/pdf/1511.06434.pdf), [Variational Autoencoder (also Deep and Convolutional)](http://arxiv.org/pdf/1312.6114v10.pdf) and [DRAW: A Recurrent Neural Network For Image Generation](http://arxiv.org/pdf/1502.04623v2.pdf). ## Run VAE/GAN: ```bash python main.py --working_directory /tmp/gan --model vae ``` DRAW: ```bash python main-draw.py --working_directory /tmp/gan ``` Deep Convolutional Generative Adversarial Networks produce decent results after 10 epochs using default parameters. ###TODO: - [ ] More complex data. - [ ] Add [Adversarial Autoencoder](http://arxiv.org/pdf/1511.05644.pdf) - [ ] Replace current attention mechanism with Spatial Transformer Layer
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3912f465c57e0f0f, topic:gan, desc:image generation, readme:image generation
matched fp:3912f465c57e0f0f, topic:tensorflow
