GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets

TL;DR

GraphSL is an open-source library that provides tools and benchmark datasets for studying and evaluating graph source localization methods, facilitating research in inverse graph diffusion problems.

Contribution

It introduces a comprehensive library and benchmark datasets for graph source localization, supporting exploration of diffusion models and evaluation of localization approaches.

Findings

Provides a versatile platform for simulating graph diffusions.

Enables benchmarking of source localization algorithms.

Supports exploration of various diffusion models.

Abstract

We introduce GraphSL, a new library for studying the graph source localization problem. graph diffusion and graph source localization are inverse problems in nature: graph diffusion predicts information diffusions from information sources, while graph source localization predicts information sources from information diffusions. GraphSL facilitates the exploration of various graph diffusion models for simulating information diffusions and enables the evaluation of cutting-edge source localization approaches on established benchmark datasets. The source code of GraphSL is made available at Github Repository (https://github.com/xianggebenben/GraphSL). Bug reports and feedback can be directed to the Github issues page (https://github.com/xianggebenben/GraphSL/issues).