Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the largest possible models to see what capabilities might appear. Today, the ...

Research and innovation in Texas A&M University's biomedical engineering department often centers around clinical impact on ...

Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven ...

A pair of newly developed models may help better predict outcomes in patients with diffuse large B-cell lymphoma (DLBCL). The ...

A mathematics professor at The University of Manchester has developed a novel machine-learning method to detect sudden changes in fluid behaviour, improving speed and cost of identifying these ...

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during ...

Large language models lack grounding in physical causality — a gap world models are designed to fill. Here's how three distinct architectural approaches (JEPA, Gaussian splats, and end-to-end ...