Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

Despite the AI hype, ML tools really are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and increasingly complex transistor structures are driving a steady ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, saving time and resources.

While traditional landslide prediction methods often rely solely on rainfall intensity, the new approach integrates various water-related processes with a machine-learning model.

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

Applying machine learning to genome-wide association and electronic health record data may usher in a new era of precision in ...

Nuwellis's design enables systems to account for density via user input, machine measurement, or derived data for more accurate volumetric flow tracking, the company said.