Abstract: Influence maximization (IM) aims to select a seed set of users that maximizes the expected influence spread and is a fundamental problem in social network analysis. The dynamic and complex ...

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG’s ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

A Python program that tests network connectivity and latency to any host or IP address. The tool performs comprehensive network diagnostics and outputs results to a text file.

In nature, random fiber networks such as some of the tissues in the human body, are strong and tough with the ability to hold together but also stretch a lot before they fail. Studying this structural ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

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 ...

Installing Python and related applications on a system without a network connection isn’t easy, but you can do it. Here’s how. The vast majority of modern software development revolves around one big ...

Cybersecurity researchers have detailed an attack that involved a threat actor utilizing a Python-based backdoor to maintain persistent access to compromised endpoints and then leveraged this access ...