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 ...
Jacob Holm was flipping through proofs from an October 2019 research paper he and colleague Eva Rotenberg—an associate professor in the department of applied mathematics and computer science at the ...
The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...
GeekWire chronicles the Pacific Northwest startup scene. Sign up for our weekly startup newsletter, and check out the GeekWire funding tracker and VC directory. by John Cook on May 14, 2013 at 4:30 am ...
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 ...
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 ...
Abstract: The speed of algorithms on massive graphs depends on the size of the given data. Grammar-based compression is a technique to compress the size of a graph while still allowing to read or to ...
The Saint Louis University Department of Computer Science offers courses at the undergraduate and graduate level. Content below is provided by SLU Academic Catalog. A broad survey of the computer ...
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