What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, ...

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability, particularly ...

Virtual echocardiography screening tool scores calculated via algorithm matched manually calculated scores and are promising ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin ...

AI & automation are revolutionizing materials discovery, enabling faster, and more sustainable breakthroughs across scientific fields.

Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations.D ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

An experimental study shows that already small-scale quantum computers can boost the performance of machine learning algorithms.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...

This consists of 15 biochemical tests, including serum phosphate. Our aim was to understand if abnormalities in serum phosphate could be predicted, using a machine learning algorithm (MLA) by other ...

This article explores the top 10 ML algorithms essential for quality assurance, from Decision Trees for defect prediction to Neural Networks for automated test generation, helping test engineers ...