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NBVAE
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Negative-Binomial VAE for discrete data
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Download README
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README.md
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NBVAE
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# NBVAE This is the demo code for the paper "Variational Autoencoders for Sparse and Overdispersed Discrete Data" in AISTATS 2020 [Link](http://proceedings.mlr.press/v108/zhao20c.html). # Datasets The datasets of 20NG and ML-10M are provided. The other text data can be downloaded from the code repo of [DPFA](https://github.com/zhegan27/dpfa_icml2015). The other collaborative-filtering data can be downloaded from the links in the paper and preprocessed with the code of [MultiVAE](https://github.com/dawenl/vae_cf). # Installation & Set-Up The code is implemented with Python 3.5.2 and Tensorflow 1.10.0, and also requires Numpy, Scipy, Scikit-learn, Pandas, and Bottleneck installations. # Run the demos The demos of NBVAE and NBVAE_dm on text data are in ```demo_NBVAE.sh```. The demo of NBVAE_b on binary collaborative-filtering data is in ```demo_NBVAE_b.sh```.
