Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design ...

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 ...

A research team led by Prof. Wan Yinhua from the Institute of Process Engineering (IPE) of the Chinese Academy of Sciences ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

The paper offers up 13 areas where machine learning can be deployed, including energy production, CO 2 removal, education, solar geoengineering, and finance.Within these fields, the possibilities ...

Health research is increasingly turning to high-throughput molecular datasets (also known as ‘omic’ datasets) to discover novel biomarkers of disease risk and outcome. Unfortunately, the size and ...

Hence, our methods alleviate the heterogeneity often encountered in real-world distributed learning applications. Throughout extensive numerical experimentation, we demonstrate that our clustering ...