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Bayesian inference of transition matrices from incomplete graph data with a topological prior
Many network analysis and graph learning techniques are based on discrete- or continuous-time models of random walks. To apply these methods, it is necessary to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, where weighted edges...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567898/ https://www.ncbi.nlm.nih.gov/pubmed/37840552 http://dx.doi.org/10.1140/epjds/s13688-023-00416-3 |