Skip to content

Variational Autoencoders for Collaborative Filtering - Implementation in PyTorch

Notifications You must be signed in to change notification settings

BingshuiDa/vae-cf-pytorch

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

vae-cf-pytorch

An Implementation of Variational Autoencoders for Collaborative Filtering (Liang et al. 2018) in PyTorch.

This repo gives you an implementation of VAE for Collaborative Filtering in PyTorch. It's model is quite simple but powerful so i made a success reproducing it with PyTorch. Every data preprocessing step and code follows exactly from Authors' Repo.

I implemented MultiDAE too but didn't test it so MultiDAE is excluded from main.py but its code is available in models.py

Requirements

PyTorch 0.4 & Python 3.6
Numpy
TensorboardX

Examples

python main.py --cuda for full training.

Dataset

You should execute python data.py first to download necessary data and preprocess MovieLens-20M dataset.

Results

About

Variational Autoencoders for Collaborative Filtering - Implementation in PyTorch

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%