Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...
Abstract: In the practical use of graph databases, storing graphs separately enhances maintainability, while integrating them into a unified graph facilitates advanced analytics. To address these dual ...
Abstract: Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost.
A professionally curated list of awesome resources (paper, code, data, etc.) on Deep Graph Anomaly Detection (DGAD), which is the first work to comprehensively and systematically summarize the recent ...
The code accompanies paper Graph reduction with spectral and cut guarantees by Andreas Loukas published at JMLR/2019. Can one reduce the size of a graph without significantly altering its basic ...
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