Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing ...

I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the ...

A digital innovation initiative about fault anomalies has been selected as one of the first projects for the new Microsoft AI ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, molecules, and materials.

In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is ...

While AI-driven approaches tout increased speed and lower costs, commercial interests compromise scientific collaboration.

This course will cover a wide range of machine learning methods, both model-based and algorithmic.

Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms.

Discover why robots excel at math but struggle with human-like tasks. Explore Moravec's Paradox and the future of adaptable ...