Carsten Riggelsen

发表

Bayesian networks for tsunami early warning

Frank Scherbaum, Lilian Blaser, Matthias Ohrnberger, 2011 .

Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions

Carsten Riggelsen, C. Riggelsen, 2006, SDM.

Learning Bayesian Network Models from Incomplete Data using Importance Sampling

A. J. Feelders, Carsten Riggelsen, 2005, AISTATS.

A Machine Learning Approach for Improving the Detection Capabilities at 3C Seismic Stations

Matthias Ohrnberger, Carsten Riggelsen, C. Riggelsen, 2014, Pure and Applied Geophysics.

On the use of Bayesian networks for Probabilistic Seismic Hazard Analysis

Frank Scherbaum, Carsten Riggelsen, Nicolas Kuehn, 2011 .

Learning aggregations of ground-motion models using data

Frank Scherbaum, Carsten Riggelsen, Nikolaos Gianniotis, 2011 .

Approximation Methods for Efficient Learning of Bayesian Networks

Carsten Riggelsen, C. Riggelsen, 2008, Frontiers in Artificial Intelligence and Applications.

Graphical Models as Surrogates for Complex Ground Motion Models

Frank Scherbaum, Carsten Riggelsen, Kristin Vogel, 2012, ICAISC.

Visualisation of high-dimensional data using an ensemble of neural networks

Carsten Riggelsen, Nikolaos Gianniotis, C. Riggelsen, 2013, 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL).

Autoencoding Ground Motion Data for Visualisation

Frank Scherbaum, Carsten Riggelsen, Nikolaos Gianniotis, 2012, ICANN.

Quantification of epistemic uncertainties in probabilistic seismic hazard analysis

Frank Scherbaum, Matthias Ohrnberger, Carsten Riggelsen, 2011 .

Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals

Frank Scherbaum, Matthias Ohrnberger, Carsten Riggelsen, 2007, PKDD.

Learning Bayesian Networks: A MAP Criterion for Joint Selection of Model Structure and Parameter

Carsten Riggelsen, C. Riggelsen, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Proceedings of the 2008 conference on Approximation Methods for Efficient Learning of Bayesian Networks

Carsten Riggelsen, 2008 .

How useful are complex flood damage models?

Bruno Merz, Heidi Kreibich, Frank Scherbaum, 2014 .

Ensembles of Ground Motion Models

Frank Scherbaum, Carsten Riggelsen, Nikos Gianniotis, 2011 .

The application of Bayesian networks in natural hazard analyses

Frank Scherbaum, Carsten Riggelsen, Kristin Vogel, 2013 .

Modeling the Joint Probability of Earthquake, Site, and Ground-Motion Parameters Using Bayesian Networks

Frank Scherbaum, Carsten Riggelsen, Nicolas Kuehn, 2011 .

Bayesian Belief Network for Tsunami Warning Decision Support

Frank Scherbaum, Lilian Blaser, Matthias Ohrnberger, 2009, ECSQARU.

MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition

Carsten Riggelsen, 2005, ECML.

Improving the Accuracy of Automatic Detections at Seismic Stations via Machine Learning

Matthias Ohrnberger, Carsten Riggelsen, 2010 .

Bayesian network learning for natural hazard analyses

Frank Scherbaum, Carsten Riggelsen, Kristin Vogel, 2014 .

Unsupervised Feature Selection for Pattern Discovery in Seismic Wavefields

Frank Scherbaum, Matthias Ohrnberger, Carsten Riggelsen, 2008, FSDM.

An Interactive Tool for the Elicitation of Subjective Probabilities in Probabilistic Seismic-Hazard Analysis

Frank Scherbaum, Carsten Riggelsen, Andrew Curtis, 2013 .

Learning Task Relatedness via Dirichlet Process Priors for Linear Regression Models

Carsten Riggelsen, Marcel Hermkes, Nicolas Kühn, 2012, ESANN.

Information Sharing Between Ground Motion Models from Different Regions via Dirichlet Process Priors

Carsten Riggelsen, Marcel Hermkes, Kristin Vogel, 2012 .

Learning parameters of Bayesian networks from incomplete data via importance sampling

Carsten Riggelsen, C. Riggelsen, 2006, Int. J. Approx. Reason..

Applications of Bayesian Networks in Geo-Sciences

Bruno Merz, Frank Scherbaum, Carsten Riggelsen, 2013 .

Information-Theoretic Selection of Ground-Motion Prediction Equations for Seismic Hazard Analysis: An Applicability Study Using Californian Data

Frank Scherbaum, Carsten Riggelsen, Nicolas Kuehn, 2009 .

Challenges for Bayesian network learning in a flood damage assessment application

Bruno Merz, Heidi Kreibich, Frank Scherbaum, 2014 .

Simultaneous quantification of epistemic and aleatory uncertainty in GMPEs using Gaussian process regression

Carsten Riggelsen, Marcel Hermkes, C. Riggelsen, 2014, Bulletin of Earthquake Engineering.