Ulster University

Accelerating your Research using the Northern Ireland HPC cluster: Hands-on guide with GPU and CPU-based applications - Part 2

This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.
Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
GitHub

City2Graph: GeoAI with Graph Neural Networks (GNNs) and Spatial Network Analysis

This installs the core functionality without PyTorch and PyTorch Geometric. To use PyTorch and PyTorch Geometric with City2Graph installed from conda-forge, you need to manually add these libraries to ...
GitHub

Simple Neural Network Models

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 ...
IEEE

HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion

Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...
Hosted on MSN

Build a deep neural network from scratch in Python

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 ...
IEEE

A Neural Network-Based ADC Calibration Framework via Quantization Code Reconstruction

Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...