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Found 5 papers, 1 papers with code
Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks
FairGI employs the similarity matrix of individuals to achieve individual fairness within groups, while leveraging adversarial learning to address group fairness in terms of both Equal Opportunity and Statistical Parity.
Recent Advances in Text Analysis
In particular, we propose a new statistical model for ranking the citation impacts of $11$ topics, and we also build a cross-topic citation graph to illustrate how research results on different topics spread to one another.
Co-embedding of Nodes and Edges with Graph Neural Networks
CensNet is a general graph embedding framework, which embeds both nodes and edges to a latent feature space.
Spectral Algorithms for Community Detection in Directed Networks
Community detection in large social networks is affected by degree heterogeneity of nodes.
CensNet: Convolution with Edge-Node Switching in Graph Neural Networks
In this paper, we present CensNet, Convolution with Edge-Node Switching graph neural network, for semi-supervised classification and regression in graph-structured data with both node and edge features.
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Graph Regression
on Tox21
