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 ...

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 ...

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.

In this paper, we study graph contrastive learning in the context of biomedical domain, where molecular graphs are present. We propose a novel framework called MoCL, which utilizes domain knowledge at ...

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.

US Treasury Secretary Scott Bessent said Monday he is confident the Supreme Court will back President Trump's use of a 1977 emergency law to impose broad tariffs, but noted the administration has ...

Missense variants in the O-GlcNAc transferase ( OGT) gene have recently been shown to segregate with a syndromic form of intellectual disability (OGT-ID), underscoring the importance of protein ...