This is the demo code for the paper "Variational Autoencoders for Sparse and Overdispersed Discrete Data" in AISTATS 2020 Link.
The datasets of 20NG and ML-10M are provided.
The other text data can be downloaded from the code repo of DPFA.
The other collaborative-filtering data can be downloaded from the links in the paper and preprocessed with the code of MultiVAE.
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.
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.