IdmGAE: Importance-Inspired Dynamic Masking for Graph Autoencoders.
Ge Chen|Yulan Hu|Sheng Ouyang|Zhirui Yang|Yong Liu|Cuicui Luo
| Anthology ID: | DBLP:conf/sigir/ChenHOY0L24 |
|---|---|
| Volume: | Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024 |
| Year: | 2024 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2457-2461 |
| URL: | https://doi.org/10.1145/3626772.3657913 |
| DOI: | https://doi.org/10.1145/3626772.3657913 |
| DBLP: | conf/sigir/ChenHOY0L24 |
| BibTeX: |
@inproceedings{chen-2024-idmgae,
author = {Ge Chen and
Yulan Hu and
Sheng Ouyang and
Zhirui Yang and
Yong Liu and
Cuicui Luo},
editor = {Grace Hui Yang and
Hongning Wang and
Sam Han and
Claudia Hauff and
Guido Zuccon and
Yi Zhang},
title = {{IdmGAE: Importance-Inspired Dynamic Masking for Graph Autoencoders}},
booktitle = {{Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024}},
pages = {2457--2461},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3626772.3657913},
doi = {https://doi.org/10.1145/3626772.3657913}
}