Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in convolutional neural networks. This tutorial explains the intuition, mathematical ...

One of the key findings is that raw accuracy in laboratory conditions does not guarantee stability in deployment. The study ...

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

A Slovak research team has developed a mathematical model for determining the optimum tilt angle of a solar system ranging from 0° to 90°. Their framework was tested on an experimental setup in ...

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

Artificial neural networks based on these biomarkers demonstrated strong predictive ability for AAV risk, validated across multiple data sets and patient renal biopsy samples.

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...