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Found 3 papers, 1 papers with code
Few-shot Network Anomaly Detection via Cross-network Meta-learning
Network anomaly detection aims to find network elements (e. g., nodes, edges, subgraphs) with significantly different behaviors from the vast majority.
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
The proposed JuryGCN is capable of quantifying uncertainty deterministically without modifying the GCN architecture or introducing additional parameters.
GENIUS: A Novel Solution for Subteam Replacement with Clustering-based Graph Neural Network
Subteam replacement is defined as finding the optimal candidate set of people who can best function as an unavailable subset of members (i. e., subteam) for certain reasons (e. g., conflicts of interests, employee churn), given a team of people embedded in a social network working on the same task.
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