Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

Understanding molecular diversity is fundamental to biomedical research and diagnostics, but existing analytical tools ...

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Researchers at the School of Engineering and Applied Sciences have developed a wearable sensor system capable of estimating ...

A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups at risk of being mistreated.

The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation defense by Elyas Irankhah on: "Machine Learning and Causal Inference for ...

Dive deep into the Muon Optimizer and learn how it enhances dense linear layers using the Newton-Schulz method combined with ...

Researchers at University of Tsukuba have developed a technology for real-time estimation of the valence state and growth rate of iron oxide thin films during their formation. This novel technology ...

Managing a power grid is like trying to solve an enormous puzzle. Grid operators must ensure the proper amount of power is ...

There are over 100 invasive plant species in Connecticut wreaking havoc on the state’s forests and waterways, but new technology may help ensure new species never get a chance to invade in the first ...