Cargando…
Approximate Bayesian inference in semi-mechanistic models
Inference of interaction networks represented by systems of differential equations is a challenging problem in many scientific disciplines. In the present article, we follow a semi-mechanistic modelling approach based on gradient matching. We investigate the extent to which key factors, including th...
Autores principales: | Aderhold, Andrej, Husmeier, Dirk, Grzegorczyk, Marco |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089672/ https://www.ncbi.nlm.nih.gov/pubmed/32226236 http://dx.doi.org/10.1007/s11222-016-9668-8 |
Ejemplares similares
-
Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration
por: Grzegorczyk, Marco, et al.
Publicado: (2017) -
Approximate Bayesian Inference
por: Alquier, Pierre
Publicado: (2020) -
Gradient Matching Methods for Computational Inference in Mechanistic Models for Systems Biology: A Review and Comparative Analysis
por: Macdonald, Benn, et al.
Publicado: (2015) -
Statistical inference in mechanistic models: time warping for improved gradient matching
por: Niu, Mu, et al.
Publicado: (2017) -
Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle
por: Borowska, Agnieszka, et al.
Publicado: (2022)