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Found 4 papers, 3 papers with code
Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters
Both the jumps and the diffusion distances react to classification errors (i. e. they are learnable).
Ranked #1 on
Node Classification
on Chameleon
OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters
Augmented Reality or AR filters on selfies have become very popular on social media platforms for a variety of applications, including marketing, entertainment and aesthetics.
DiffWire: Inductive Graph Rewiring via the Lovász Bound
Graph Neural Networks (GNNs) have been shown to achieve competitive results to tackle graph-related tasks, such as node and graph classification, link prediction and node and graph clustering in a variety of domains.
Ranked #1 on
Graph Classification
on IMDB-BINARY
On the Interplay between Strong Regularity and Graph Densification
In this paper we analyze the practical implications of Szemer\'edi's regularity lemma in the preservation of metric information contained in large graphs.
