To classify nodes in a newly-collected unlabeled graph, it is desirable to transfer label information from an existing labeled graph. To address this cross-graph node classification problem, we ...

Path finding in a graph. Contribute to anvaka/ngraph.path development by creating an account on GitHub.

Graph embedding aims at learning vertex representations in a low-dimensional space by distilling information from a complex-structured graph. Recent efforts in graph embedding have been devoted to ...

"We had a big, I don't know, existential crisis among students a few years back," Jure Leskovec told Fortune, "when it kind ...

Find out how today's engineers succeed by growing their technical abilities, improving how they communicate, and staying open ...

Amid the chaos of revolutionary France, one man’s mathematical obsession gave way to a calculation that now underpins much of ...

Domain Adversarial Graph Convolutional network (DAGCN) This code is about the implementation of Domain Adversarial Graph Convolutional Network for Fault Diagnosis Under Variable Working Conditions.

Agile rituals are great, but without tracking constraints and dependencies live, your transformation will stall.

"Finding chain covers of chordal-bipartite graphs," (invited) Eastern Section Meeting of the AMS, Stevens Institute of Technology, April 2007. "Transitive subtournaments of tournaments with a given ...

On Wednesday, Trump said the US may have to "unwind" existing trade deals, including with the European Union, Japan, and South Korea, if the Supreme Court doesn't uphold the tariffs.

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