Hyperbolic (ordinary and variational) autoencoders for recommender systems
Accompanying code for the paper Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks, accepted at ACM RecSys 2020.
Results
Data
To reproduce our code, please put the corresponding data files in the following folder structure:
data
- troublinganalysis
- mvae
- netflix
- ml20m
- neumf
- ml1m
- mvae
- recvae
- ml20m
Also, please install geoopt package geoopt for Riemannian optimization and hyptorch for computations in hyperbolic spaces.
Wandb
In our experiments, we have used wandb framework for result tracking. Our test scripts are based on wandb configs.
Acknowledgments
In our code we have used the following repositories: