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Found 4 papers, 3 papers with code
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms
To facilitate the benchmarking of different methods, we present a novel Snakemake workflow, called Benchpress for producing scalable, reproducible, and platform-independent benchmarks of structure learning algorithms for probabilistic graphical models.
Sequential sampling of junction trees for decomposable graphs
On the other hand, the junction-tree collapser provides a complementary operation for removing vertices in the underlying decomposable graph of a junction tree, while maintaining the junction tree property.
Statistics Theory Discrete Mathematics Combinatorics Statistics Theory
Bayesian inference in decomposable graphical models using sequential Monte Carlo methods
The theoretical properties of the algorithm are investigated, showing in particular that the refreshment step improves the algorithm performance in terms of asymptotic variance of the estimated distribution.
Statistics Theory Statistics Theory
A Prior Distribution over Directed Acyclic Graphs for Sparse Bayesian Networks
The main contribution of this article is a new prior distribution over directed acyclic graphs, which gives larger weight to sparse graphs.
