Abstract: This letter introduces a novel approach for graph classification in the context of sensor network data analysis using machine learning methods. It is based on exploiting both sensor ...
Abstract: Many modern classification problems involve data that live in high-dimensional spaces but exhibit strong low-dimensional structure. Motivated by the manifold hypothesis, this talk presents a ...
PyTorch Geometric Knowledge Graph Builder is a serverless pipeline that transforms raw RDF data from multiple heterogeneous sources into enriched knowledge graphs and constructs PyTorch Geometric ...
ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Abstract: Graph neural networks (GNNs) have demonstrated outstanding performance in graph classification tasks. Most existing GNNs designed for graph classification adopt a structure that combines ...
Graphs provide a powerful tool for coping with the non-uniformity and irregularity of 3D meshes, enabling multi-scale representations of 3D data. However, many existing methods either neglect the ...
Primary immunodeficiency disorders (PIDs) are a heterogeneous group of disorders characterized, as the name suggests, by deficiencies (abnormal, poor or absent function) in the immune system. As ...