Abstract: To address the issue of limited topological generalization in Graph Attention Networks (GAT) due to the fixed hop range, this paper proposes a Random-K-Hop Graph Attention Network (RKGAT) to ...

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.

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 ...

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.

PyScanNet is a powerful and versatile network scanner implemented in Python, designed to facilitate comprehensive network reconnaissance and analysis. Leveraging the robust capabilities of Python, ...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...