Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models have shown strong ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

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. - ...

This week’s Top 10 looks at the applications of machine learning in the energy sector, spotlighting those leading the way ...

For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...

Machine learning is changing the front end of drug discovery, where researchers decide which targets to pursue and which molecules deserve costly laboratory work. Its deeper test lies further ...