Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...

Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

Scientist Yi Nian is sharing his machine-learning expertise with the world in his latest co-authored publication, “Globally Interpretable Graph Learning via Distribution Matching.” SEATTLE, Wash. - ...

Graph-based machine learning is the next wave of digital disruption Machine learning has been getting a lot of attention over the last year or so. This is partly because a variety of companies have ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...

Machine learning can sound pretty complicated, right? Like something only super-smart tech people get. But honestly, it’s ...

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...

This year’s coveted Tao Li Award has gone to Jundong Li, an associate professor of electrical and computer engineering and computer science at the University of Virginia. Li, feeling “genuinely ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...