Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction.
Aravind Sankar|Xinyang Zhang|Adit Krishnan|Jiawei Han
| Anthology ID: | DBLP:conf/wsdm/SankarZK020 |
|---|---|
| Volume: | WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020 |
| Year: | 2020 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 510-518 |
| URL: | https://doi.org/10.1145/3336191.3371811 |
| DOI: | https://doi.org/10.1145/3336191.3371811 |
| DBLP: | conf/wsdm/SankarZK020 |
| BibTeX: |
@inproceedings{sankar-2020-infvae,
author = {Aravind Sankar and
Xinyang Zhang and
Adit Krishnan and
Jiawei Han},
editor = {James Caverlee and
Xia Ben Hu and
Mounia Lalmas-Roelleke and
Wei Wang},
title = {{Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction}},
booktitle = {{WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020}},
pages = {510--518},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3336191.3371811},
doi = {https://doi.org/10.1145/3336191.3371811}
}