Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels.

Qingqing Long|Yilun Jin|Yi Wu|Guojie Song


Anthology ID:DBLP:conf/www/LongJWS21
Volume:WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021.
Year:2021
Venue:The Web Conference (WWW)
Publisher:ACM / IW3C2
Pages:1204-1214
URL:https://doi.org/10.1145/3442381.3449951
DOI:https://doi.org/10.1145/3442381.3449951
DBLP:conf/www/LongJWS21
BibTeX:
@inproceedings{long-2021-theoretically, author = {Qingqing Long and Yilun Jin and Yi Wu and Guojie Song}, editor = {Jure Leskovec and Marko Grobelnik and Marc Najork and Jie Tang and Leila Zia}, title = {{Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels}}, booktitle = {{WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021}}, pages = {1204--1214}, publisher = {ACM / IW3C2}, year = {2021}, url = {https://doi.org/10.1145/3442381.3449951}, doi = {https://doi.org/10.1145/3442381.3449951} }