Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...

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 ...

Previously, S&P only had data on about 2 million SMEs, but its AI-powered RiskGauge platform expanded that to 10 million.

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

In this work, we present an approach that integrates theoretical spectral calculations with machine learning to identify PAHs, an approach that can be extended straightforwardly to the thousands of ...

In this paper, we propose an offline anomaly detection using machine learning in ROS 2. Our methodology leverages the widely adopted ros2_tracing framework for efficient and automated data collection, ...

A University of Cincinnati study found machine learning models can aid in the automation and detection of abnormal brain activity sometimes referred to as a "brain tsunami." ...

Methodology This study employs a machine learning approach to predict Autism Spectrum Disorder (ASD) using the XGBoost algorithm, a gradient-boosting framework optimised for structured data ...