Abstract: Artificial neural networks (ANNs) are intricate mathematical models, drawing inspiration from the biological nervous system, and offering intelligence alongside nonparametric capabilities.

To address the issues of strong subjectivity and difficulty in feature extraction that are inherent to traditional frequency response analysis methods used for diagnosing transformer winding ...

Abstract: Gaussian processes (GPs) have attracted considerable attention in assisting evolutionary algorithms (EAs) to solve computationally expensive optimization problems (EOPs) because they can ...

Learn how to build a perceptron from scratch in Python! This tutorial covers the theory, coding, and practical examples, helping you understand the foundations of neural networks and machine learning.

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...

The original version of this story appeared in Quanta Magazine. Computer scientists often deal with abstract problems that are hard to comprehend, but an exciting new algorithm matters to anyone who ...