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Found 4 papers, 1 papers with code
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.
Ranked #1 on
Graph Regression
on Tox21
