MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.
Jinjia Feng|Zhen Wang|Yaliang Li|Bolin Ding|Zhewei Wei|Hongteng Xu
| Anthology ID: | DBLP:conf/cikm/FengWLDWX22 |
|---|---|
| Volume: | Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 509-519 |
| URL: | https://doi.org/10.1145/3511808.3557395 |
| DOI: | https://doi.org/10.1145/3511808.3557395 |
| DBLP: | conf/cikm/FengWLDWX22 |
| BibTeX: |
@inproceedings{feng-2022-mgmae,
author = {Jinjia Feng and
Zhen Wang and
Yaliang Li and
Bolin Ding and
Zhewei Wei and
Hongteng Xu},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {509--519},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557395},
doi = {https://doi.org/10.1145/3511808.3557395}
}