37 citations · 135 across the 12 of their papers we have counts for
5 papers · 1 filter
Testing for Causality in Continuous Time Bayesian Network Models of High-Frequency Data
Jonas Hallgren, Timo Koski
Continuous time Bayesian networks are investigated with a special focus on their ability to express causality. A framework is presented for doing inference in these networks. The c…
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…
Context-specific independence in graphical log-linear models
Henrik Nyman, Johan Pensar, Timo Koski +1
Log-linear models are the popular workhorses of analyzing contingency tables. A log-linear parameterization of an interaction model can be more expressive than a direct parameteriz…
Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models
Johan Pensar, Henrik Nyman, Timo Koski +1
We introduce a novel class of labeled directed acyclic graph (LDAG) models for finite sets of discrete variables. LDAGs generalize earlier proposals for allowing local structures i…
Stratified Graphical Models - Context-Specific Independence in Graphical Models
Henrik Nyman, Johan Pensar, Timo Koski +1
Theory of graphical models has matured over more than three decades to provide the backbone for several classes of models that are used in a myriad of applications such as genetic…