References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
Sorted by year (citations)

  1. Bojan Mihaljević, Concha Bielza, Pedro Larrañaga: bnclassify: Learning Bayesian Network Classifiers (2018) not zbMATH
  2. Bryon Aragam, Jiaying Gu, Qing Zhou: Learning Large-Scale Bayesian Networks with the sparsebn Package (2017) arXiv
  3. Datta, Sagnik; Gayraud, Ghislaine; Leclerc, Eric; Bois, Frederic Y.: \itGraph_sampler: a simple tool for fully Bayesian analyses of DAG-models (2017)
  4. Masegosa, Andrés R.; Feelders, Ad J.; van der Gaag, Linda C.: Learning from incomplete data in Bayesian networks with qualitative influences (2016)
  5. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
  6. Barclay, L. M.; Hutton, J. L.; Smith, J. Q.: Refining a Bayesian network using a chain event graph (2013)
  7. Cordone, Roberto; Lulli, Guglielmo: An integer optimization approach for reverse engineering of gene regulatory networks (2013)
  8. Højsgaard, Søren; Edwards, David; Lauritzen, Steffen: Graphical models with R. (2012)
  9. Markus Kalisch; Martin Mächler; Diego Colombo; Marloes Maathuis; Peter Bühlmann: Causal Inference Using Graphical Models with the R Package pcalg (2012) not zbMATH
  10. Jaroszewicz, Szymon; Scheffer, Tobias; Simovici, Dan A.: Scalable pattern mining with Bayesian networks as background knowledge (2009) ioport
  11. Marco Scutari: Learning Bayesian Networks with the bnlearn R Package (2009) arXiv
  12. Angelopoulos, Nicos; Cussens, James: Bayesian learning of Bayesian networks with informative priors (2008)
  13. Ben Hassen, Hanen; Masmoudi, Afif; Rebai, Ahmed: Causal inference in biomolecular pathways using a Bayesian network approach and an implicit method (2008)
  14. Claus Dethlefsen; Søren Højsgaard: A Common Platform for Graphical Models in R: The gRbase Package (2005) not zbMATH