5 citations · 11 across the 5 of their papers we have counts for
5 papers
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms
Felix L. Rios, Giusi Moffa, Jack Kuipers
Describing the relationship between the variables in a study domain and modelling the data generating mechanism is a fundamental problem in many empirical sciences. Probabilistic g…
Sequential sampling of junction trees for decomposable graphs
Jimmy Olsson, Tetyana Pavlenko, Felix L. Rios
The junction-tree representation provides an attractive structural property for organizing a decomposable graph. In this study, we present two novel stochastic algorithms, which we…
Bayesian learning of weakly structural Markov graph laws using sequential Monte Carlo methods
Jimmy Olsson, Tetyana Pavlenko, Felix L. Rios
We present a sequential sampling methodology for weakly structural Markov laws, arising naturally in a Bayesian structure learning context for decomposable graphical models. As a k…
Graphical posterior predictive classifier: Bayesian model averaging with particle Gibbs
Tatjana Pavlenko, Felix Leopoldo Rios
In this study, we present a multi-class graphical Bayesian predictive classifier that incorporates the uncertainty in the model selection into the standard Bayesian formalism. For…
A Prior Distribution over Directed Acyclic Graphs for Sparse Bayesian Networks
Felix L. Rios, John M. Noble, Timo J. T. Koski
The main contribution of this article is a new prior distribution over directed acyclic graphs, which gives larger weight to sparse graphs. This distribution is intended for struct…