“Testing and control sit at the center of how complex hardware is developed and deployed, but the tools supporting that work haven’t kept pace with system complexity,” said Revel founder and CEO Scott ...

Key advances in the development of artificial neural networks came from psychologists seeking to understand how the human mind works.

When Covid-19 struck in 2020, Sashikumaar Ganeshan at the Indian Institute of Science, Bangalore built a model to predict the spread of the contagion, marking his deep immersion into AI technologies.

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Abstract: Deep learning architectures have brought about new heights in computer vision, with the most common approach being the Convolutional Neural Network (CNN). Through CNN, tasks previously ...

Abstract: In this study, we present a novel approach to adversarial attacks for graph neural networks (GNNs), specifically addressing the unique challenges posed by graphical data. Unlike traditional ...