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20112020
most citedModel selection and parameter inference in phylogenetics using Nested Sampling

225 citations · 241 across the 7 of their papers we have counts for

collaborators

9 papers

math.CO2020

Combinatorial perspectives on Dollo- characters in phylogenetics

Remco Bouckaert, Mareike Fischer, Kristina Wicke

Recently, the perfect phylogeny model with persistent characters has attracted great attention in the literature. It is based on the assumption that complex traits or characters ca…

q-bio.PE2019

Bayesian inference of species trees using diffusion models

Marnus Stoltz, Boris Bauemer, Remco Bouckaert +3

We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried…

q-bio.QM2017★ 225 cited

Model selection and parameter inference in phylogenetics using Nested Sampling

Patricio Maturana, Brendon J. Brewer, Steffen Klaere +1

Bayesian inference methods rely on numerical algorithms for both model selection and parameter inference. In general, these algorithms require a high computational effort to yield…

cs.AI2013

Optimizing Causal Orderings for Generating DAGs from Data

Remco R. Bouckaert

An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is presented. The algorithm manipulates the ordering of the v…

cs.AI2013

A Stratified Simulation Scheme for Inference in Bayesian Belief Networks

Remco R. Bouckaert

Simulation schemes for probabilistic inference in Bayesian belief networks offer many advantages over exact algorithms; for example, these schemes have a linear and thus predictabl…

cs.AI2013★ 1 cited

Properties of Bayesian Belief Network Learning Algorithms

Remco R. Bouckaert

Bayesian belief network learning algorithms have three basic components: a measure of a network structure and a database, a search heuristic that chooses network structures to be c…