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Carsten Riggelsen
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2010 – 2019
- 2013
- [c11]Nikolaos Gianniotis, Carsten Riggelsen:
Visualisation of high-dimensional data using an ensemble of neural networks. CIEL 2013: 17-24 - 2012
- [c10]Marcel Hermkes, Nicolas Kuehn, Carsten Riggelsen:
learning task relatedness via dirichlet process priors for linear regression models. ESANN 2012 - [c9]Kristin Vogel, Carsten Riggelsen, Nicolas Kuehn, Frank Scherbaum:
Graphical Models as Surrogates for Complex Ground Motion Models. ICAISC (2) 2012: 188-195 - [c8]Nikolaos Gianniotis, Carsten Riggelsen, Nicolas Kühn, Frank Scherbaum:
Autoencoding Ground Motion Data for Visualisation. ICANN (2) 2012: 395-402
2000 – 2009
- 2009
- [c7]Lilian Blaser, Matthias Ohrnberger, Carsten Riggelsen, Frank Scherbaum:
Bayesian Belief Network for Tsunami Warning Decision Support. ECSQARU 2009: 757-768 - 2008
- [b2]Carsten Riggelsen:
Approximation Methods for Efficient Learning of Bayesian Networks. Frontiers in Artificial Intelligence and Applications 168, IOS Press 2008, ISBN 978-1-58603-821-2, pp. 1-137 - [c6]Carsten Riggelsen:
Learning Bayesian Networks: A MAP Criterion for Joint Selection of Model Structure and Parameter. ICDM 2008: 522-529 - [c5]Andreas Köhler, Matthias Ohrnberger, Carsten Riggelsen, Frank Scherbaum:
Unsupervised Feature Selection for Pattern Discovery in Seismic Wavefields. FSDM 2008: 106-121 - 2007
- [c4]Carsten Riggelsen, Matthias Ohrnberger, Frank Scherbaum:
Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals. PKDD 2007: 565-572 - 2006
- [b1]Carsten Riggelsen:
Approximation Methods for Efficient Learning of Bayesian Networks. Utrecht University, Netherlands, 2006 - [j1]Carsten Riggelsen:
Learning parameters of Bayesian networks from incomplete data via importance sampling. Int. J. Approx. Reason. 42(1-2): 69-83 (2006) - [c3]Carsten Riggelsen:
Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions. SDM 2006: 130-140 - 2005
- [c2]Carsten Riggelsen, Ad Feelders:
Learning Bayesian Network Models from Incomplete Data using Importance Sampling. AISTATS 2005: 301-308 - [c1]Carsten Riggelsen:
MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition. ECML 2005: 329-340
Coauthor Index
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