Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Learn what overfitting is, how it impacts data models, and effective strategies to prevent it, such as cross-validation and simplification.

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...

Digital Twin of the Ocean is a continuously updated virtual counterpart of the real ocean that exchanges data in real time ...