Learning Bayesian Network Models from Incomplete Data using Importance Sampling. - Carsten Riggelsen; Ad Feelders (AISTATS, 2005)

MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition. - Carsten Riggelsen (ECML, 2005)

Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions. - Carsten Riggelsen (SDM, 2006)

Learning parameters of Bayesian networks from incomplete data via importance sampling. - Carsten Riggelsen (Int. J. Approx. Reason., 2006)

Approximation Methods for Efficient Learning of Bayesian Networks. - Carsten Riggelsen (2006)

Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals. - Carsten Riggelsen; Matthias Ohrnberger; Frank Scherbaum (PKDD, 2007)

Learning Bayesian Networks: A MAP Criterion for Joint Selection of Model Structure and Parameter. - Carsten Riggelsen (ICDM, 2008)

Unsupervised Feature Selection for Pattern Discovery in Seismic Wavefields. - Andreas Köhler; Matthias Ohrnberger; Carsten Riggelsen; Frank Scherbaum (FSDM, 2008)

Approximation Methods for Efficient Learning of Bayesian Networks - Carsten Riggelsen (IOS Press, 2008)

Bayesian Belief Network for Tsunami Warning Decision Support. - Lilian Blaser; Matthias Ohrnberger; Carsten Riggelsen; Frank Scherbaum (ECSQARU, 2009)

learning task relatedness via dirichlet process priors for linear regression models. - Marcel Hermkes; Nicolas Kuehn; Carsten Riggelsen (ESANN, 2012)

Graphical Models as Surrogates for Complex Ground Motion Models. - Kristin Vogel; Carsten Riggelsen; Nicolas Kuehn; Frank Scherbaum (ICAISC (2), 2012)

Autoencoding Ground Motion Data for Visualisation. - Nikolaos Gianniotis; Carsten Riggelsen; Nicolas Kühn; Frank Scherbaum (ICANN (2), 2012)

Visualisation of high-dimensional data using an ensemble of neural networks. - Nikolaos Gianniotis; Carsten Riggelsen (CIEL, 2013)