This notebook is a modified version of the notebook that accompanies the paper "Variational autoencoders for collaborative filtering" by Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, and Tony Jebara, in The Web Conference (aka WWW) 2018.
We modified the original code to adjust, clean and preprocess a new publicly available dataset "Yahoo! Music user ratings of musical artists, version 1.0", then trained the model and fined-tuned the hyperparameters on the new dataset.
In this notebook, we show a complete self-contained example of training a variational autoencoder (as well as a denoising autoencoder) with multinomial likelihood (described in the original paper).
This was done as the course project for the course "Deep Generative Models, Computer Science, UC Irvine, Spring 2019".