GSPBOX: A toolbox for signal processing on graphs
Nathana\"el Perraudin, Johan Paratte, David Shuman, Lionel Martin,, Vassilis Kalofolias, Pierre Vandergheynst, David K. Hammond
TL;DR
GSPBOX is a comprehensive software framework designed to facilitate signal processing tasks on graph-structured data, providing modular tools for researchers and practitioners.
Contribution
It introduces the GSPBox, a modular toolbox that organizes graph signal processing methods into an accessible software package.
Findings
Provides a structured software framework for graph signal processing
Includes key modules for various graph signal processing tasks
Enhances research and application development in graph-based data analysis
Abstract
This document introduces the Graph Signal Processing Toolbox (GSPBox) a framework that can be used to tackle graph related problems with a signal processing approach. It explains the structure and the organization of this software. It also contains a general description of the important modules.
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Taxonomy
TopicsAdvanced Graph Neural Networks · Graph Theory and Algorithms · Complex Network Analysis Techniques