For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...

Abstract: In recent years, the Graph Transformer has demonstrated superiority on various graph-level tasks by facilitating global interactions among nodes. However, as for node-level tasks, the ...

Abstract: Attributed graph clustering, aiming to discover the underlying graph structure and partition the graph nodes into several disjoint categories, is a basic task in graph data analysis.

OpenZL formalizes compression as a computational graph: nodes are codecs/graphs, edges are typed message streams, and the finalized graph is serialized with the payload. Any frame produced by any ...