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Wang et al., 2024 - Google Patents

The heterophilic snowflake hypothesis: Training and empowering gnns for heterophilic graphs

Wang et al., 2024

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Document ID
2878496468323071845
Author
Wang K
Zhang G
Zhang X
Fang J
Wu X
Li G
Pan S
Huang W
Liang Y
Publication year
Publication venue
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

External Links

Snippet

Graph Neural Networks (GNNs) have become pivotal tools for a range of graph-based learning tasks. Notably, most current GNN architectures operate under the assumption of homophily, whether explicitly or implicitly. While this underlying assumption is frequently …
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    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • G—PHYSICS
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