Scientists aiming to advance cancer diagnostics have developed a machine learning tool that is able to identify ...

Such features serve as inputs for training and testing several artificial neural networks. Statistical tests are carried out to assess the performance and to pick the best neural network ... process.

The White House released an expansive report that blames a crisis of chronic disease in children on ultraprocessed foods, chemical exposures, lack of physical activity, stress and excessive use of ...

The AI diffusion rule sorted countries into tiers and restricted the export of AI chips depending on tier. From SAS Innovate, Drew Robb is reporting on the company’s new AI tools and platform ...

In particular, we develop a novel End-To-End Mixture Clustering Attention Neural Network (MC-ANN) model for univariate time series forecasting, which we show is able to predict future reservoir water ...

Abstract: In this paper, artificial neural-network approaches to electromagnetic (EM)-based modeling in both frequency and time domains and their applications to nonlinear circuit optimization are ...

The course covers supervised classification based on e.g., artificial neural networks (deep learning), as well as unsupervised learning (clustering), regression, optimization (evolutionary algorithms ...

A collection of real-world machine learning and AI projects. Explore hands-on implementations of cutting-edge models, practical solutions, and techniques to tackle real-world challenges using AI.