Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs through layers, calculating activations, and preparing data for ...

Google Colab, also known as Colaboratory, is a free online tool from Google that lets you write and run Python code directly in your browser. It works like Jupyter Notebook but without the hassle of ...

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 ...

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...

Abstract: The practice of deep learning has shown that neural networks generalize remarkably well even with an extreme number of learned parameters. This appears to contradict traditional statistical ...

Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions, an essential aspect of solving partial differential ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

We present a Spiking Neural Network (SNN) model that incorporates learnable synaptic delays through two approaches: per-synapse delay learning via Dilated Convolutions with Learnable Spacings (DCLS) ...

Abstract: The article deals with the problem associated with the influence of a prompt composed by users on the efficiency of the generated program code. The aim of the research is to work out a ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...