On the Equivalence of Gaussian Graphical Models Defined on Complete Bipartite Graphs
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915345474781184 |
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| author | Molkaraie, Mehdi |
| author_facet | Molkaraie, Mehdi |
| contents | This paper introduces two Gaussian graphical models defined on complete bipartite graphs. We show that the determinants of the precision matrices associated with the models are equal up to scale, where the scale factor only depends on model parameters. In this context, we will introduce a notion of ``equivalence" between the two Gaussian graphical models. This equivalence has two key applications: first, it can significantly reduce the complexity of computing the exact value of the determinant, and second, it enables the derivation of closed-form expressions for the determinants in certain special cases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_02384 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the Equivalence of Gaussian Graphical Models Defined on Complete Bipartite Graphs Molkaraie, Mehdi Information Theory Computational Complexity Computation This paper introduces two Gaussian graphical models defined on complete bipartite graphs. We show that the determinants of the precision matrices associated with the models are equal up to scale, where the scale factor only depends on model parameters. In this context, we will introduce a notion of ``equivalence" between the two Gaussian graphical models. This equivalence has two key applications: first, it can significantly reduce the complexity of computing the exact value of the determinant, and second, it enables the derivation of closed-form expressions for the determinants in certain special cases. |
| title | On the Equivalence of Gaussian Graphical Models Defined on Complete Bipartite Graphs |
| topic | Information Theory Computational Complexity Computation |
| url | https://arxiv.org/abs/2505.02384 |