Despite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a ...
Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-Sib Design: A Graphical Model Perspective
N. A. Sheehan, B. Gulbrandtsen, M. S. Lund and D. A. Sorensen Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software ...
On the 8th of December 2021, M.Sc. Kari Rantanen will defend his doctoral thesis on Optimization Algorithms for Learning Graphical Model Structures. The thesis a part of research done in the ...
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