A research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. A KAIST research team has developed a new ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...
With a $9.2 million grant from Intelligence Advanced Research Projects Activity (IARPA), Prof. Andrew A. Chien will lead a team of University of Chicago computer science researchers building the ...
Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Emil Eifrem, co-founder and CEO at Neo4j. He writes on why he thinks graph ...
When Emil Eifrem, founder and CEO of Neo4j, was working for an enterprise content management startup in Sweden in the mid-2000s, he was struggling with the challenge of mapping relationships between ...
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