An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. In their study published in ...

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies ...

The framework, Information-Contrastive Learning (I-Con), connects diverse machine learning (ML) methods, offering researchers a structured system for innovation.

A machine learning framework that uses scarce and sparse experimental data to both predict and inversely design the mechanical behavior of spinodal metamaterials. Why It Matters The method enables ...

MIT researchers developed SEAL, a framework that lets language models continuously learn new knowledge and tasks.

Hongwei Li’s team from China University of Geosciences published a research article titled “scSCC: A swapped contrastive ...

Before it makes a decision, the method combines K nearest neighbors, support vector machine, and decision tree learning. Accuracy is reportedly up to 89%. September 4, 2024 Lior Kahana ...

This study, published online in Nature Communications on January 27, 2025, introduces the STAIG framework, which integrates gene expression, spatial data, and histological images without the need ...

Self-learning AI enhances behavioral analytics for detecting advanced threats and insider risks, but demands careful ...

Computing pioneer Alan Turing suggested training machines with rewards and punishments. Two computer scientists put the idea into practice in the 1980s and set the stage for the likes of ChatGPT.