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 ...
There are various types of graphs used to visually represent data, such as bar graphs, pie charts, and histograms. Chenxing Li, a postdoctoral researcher at the University of Georgia's Center for ...
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