GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866916338507710464 |
|---|---|
| author | Wang, Junxiang Zhao, Liang |
| author_facet | Wang, Junxiang Zhao, Liang |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_03724 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets Wang, Junxiang Zhao, Liang Machine Learning Social and Information Networks 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). |
| title | GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets |
| topic | Machine Learning Social and Information Networks |
| url | https://arxiv.org/abs/2405.03724 |