116 citations · 267 across the 30 of their papers we have counts for
5 papers · 1 filter
Every LWF and AMP chain graph originates from a set of causal models
Jose M. Peña
This paper aims at justifying LWF and AMP chain graphs by showing that they do not represent arbitrary independence models. Specifically, we show that every chain graph is inclusio…
Error AMP Chain Graphs
Jose M. Peña
Any regular Gaussian probability distribution that can be represented by an AMP chain graph (CG) can be expressed as a system of linear equations with correlated errors whose struc…
Marginal AMP Chain Graphs
Jose M. Peña
We present a new family of models that is based on graphs that may have undirected, directed and bidirected edges. We name these new models marginal AMP (MAMP) chain graphs because…
Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness: Extended Version
Jose M. Peña
This paper deals with chain graphs under the Andersson-Madigan-Perlman (AMP) interpretation. In particular, we present a constraint based algorithm for learning an AMP chain graph…
Combinatorial Optimization by Learning and Simulation of Bayesian Networks
Pedro Larrañaga, Ramon Etxeberria, Jose A. Lozano +1
This paper shows how the Bayesian network paradigm can be used in order to solve combinatorial optimization problems. To do it some methods of structure learning from data and simu…