As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
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 ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Upwork reports small business leaders waste 77 workdays annually on non-core tasks, causing burnout. Delegating to ...
To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.
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 ...
Astronomer is the company behind Astro, the modern data orchestration platform built on Apache Airflow. Its work sits at the intersection of workflow automation, data engineering and operational ...
Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.
From compute and talent to energy and revenue, six charts show where the U.S. leads China in AI—and why that lead could prove ...
As AI, enterprise adoption, and compliance converge, the ability to compute on sensitive data without exposing it on public ...
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