Abstract: Graph Neural Networks (GNNs) have gained momentum in graph representation learning and boosted the state of the art in a variety of areas, such as data mining (e.g., social network analysis ...
Abstract: A vast amount of textual and structural information is required for knowledge graph construction and its downstream tasks. However, most of the current knowledge graphs are incomplete due to ...
Graph paper is commonly used for plotting, well, graphs, plus other spatial and mathematical visualizations. But for Pejac, its potential goes way beyond a two-dimensional gridded surface. The artist, ...
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