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 ...

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 ...

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

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

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 ...

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

PyTorch is a deep learning framework designed to simplify AI model development. First released by Meta AI, it was built to improve the flexibility of deep learning research.

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 ...

New machine learning framework enhances precision and efficiency in metal 3D printing, advancing sustainable manufacturing. ScienceDaily . Retrieved June 11, 2025 from www.sciencedaily.com ...

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.