DualVAE (SDM'24)

This is the Pytorch implementation for our SDM 2024 paper:

Zhiqiang Guo, Guohui Li, Jianjun Li, Chaoyang Wang, Si Shi. DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation. In SDM 2024. Paper

Data

The interaction data is shared at data/.

Training logs and models

The logs and parameters are shared at log/ and models/, respectively.

Environment

pip install -r requirements.txt

Run

Run train.sh to train DualVAE:

bash train.sh

You may specify other parameters in train.sh.

Citation

@inproceedings{guo2024dualvae,
author = {Zhiqiang Guo, Guohui Li, Jianjun Li, Chaoyang Wang, Si Shi},
title = {DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation},
booktitle = {Proceedings of SDM},
pages = {xxx},
year = {2024}
}