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Found 2 papers, 1 papers with code
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning
Most existing graph neural networks (GNNs) are limited to undirected graphs, whose restricted scope of the captured relational information hinders their expressive capabilities and deployments in real-world scenarios.
Locally Differentially Private Graph Embedding
We propose LDP-GE, a novel privacy-preserving graph embedding framework, to protect the privacy of node data.
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