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Found 4 papers, 3 papers with code
Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering
Then we design an adaptive hybrid graph filter that is related to the homophily degree, which learns the node embedding based on the graph joint aggregation matrix.
HeroLT: Benchmarking Heterogeneous Long-Tailed Learning
To achieve this, we develop the most comprehensive (to the best of our knowledge) long-tailed learning benchmark named HeroLT, which integrates 13 state-of-the-art algorithms and 6 evaluation metrics on 14 real-world benchmark datasets across 4 tasks from 3 domains.
Variational Graph Generator for Multi-View Graph Clustering
The critical point of MGC is to better utilize the view-specific and view-common information in features and graphs of multiple views.
Customizing Graph Neural Networks using Path Reweighting
Specifically, the proposed CustomGNN can automatically learn the high-level semantics for specific downstream tasks to highlight semantically relevant paths as well to filter out task-irrelevant noises in a graph.
