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A Geometric Variational Approach to Bayesian Inference
We propose a novel Riemannian geometric framework for variational inference in Bayesian models based on the nonparametric Fisher–Rao metric on the manifold of probability density functions. Under the square-root density representation, the manifold can be identified with the positive orthant of the...
Gardado en:
| Publicado en: | J Am Stat Assoc |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2019
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7540671/ https://ncbi.nlm.nih.gov/pubmed/33041402 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2019.1585253 |
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