Carsten Riggelsen

14 papers A* 1A 2B 1C 1Journal 1Unranked 6
YearRankTypeTitle / Venue / Authors
2013 — conf
Visualisation of high-dimensional data using an ensemble of neural networks.
CIEL
Nikolaos Gianniotis, Carsten Riggelsen
2012 — conf
Autoencoding Ground Motion Data for Visualisation.
ICANN (2)
Nikolaos Gianniotis, Carsten Riggelsen, Nicolas Kühn, Frank Scherbaum
2012 — conf
Graphical Models as Surrogates for Complex Ground Motion Models.
ICAISC (2)
Kristin Vogel, Carsten Riggelsen, Nicolas Kuehn, Frank Scherbaum
2012 B conf
learning task relatedness via dirichlet process priors for linear regression models.
ESANN
Marcel Hermkes, Nicolas Kuehn, Carsten Riggelsen
2009 C conf
Bayesian Belief Network for Tsunami Warning Decision Support.
ECSQARU
Lilian Blaser, Matthias Ohrnberger, Carsten Riggelsen, Frank Scherbaum
2008 — book
Approximation Methods for Efficient Learning of Bayesian Networks
Carsten Riggelsen
2008 A* conf
Learning Bayesian Networks: A MAP Criterion for Joint Selection of Model Structure and Parameter.
ICDM
Carsten Riggelsen
2008 — conf
Unsupervised Feature Selection for Pattern Discovery in Seismic Wavefields.
FSDM
Andreas Köhler, Matthias Ohrnberger, Carsten Riggelsen, Frank Scherbaum
2007 — conf
Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals.
PKDD
Carsten Riggelsen, Matthias Ohrnberger, Frank Scherbaum
2006 — —
Approximation Methods for Efficient Learning of Bayesian Networks.
Carsten Riggelsen
2006 A conf
Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions.
SDM
Carsten Riggelsen
2006 J jnl
Learning parameters of Bayesian networks from incomplete data via importance sampling.
Int. J. Approx. Reason.
Carsten Riggelsen
2005 A conf
Learning Bayesian Network Models from Incomplete Data using Importance Sampling.
AISTATS
Carsten Riggelsen, Ad Feelders
2005 — conf
MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition.
ECML
Carsten Riggelsen
2025 Best paper conf
Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja.
CheckMATE
Nicolò Altamura, Enrico Bragastini, Marco Campion, Mila Dalla Preda
2026 Best paper preprint
ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage.
arXiv
Chang Liu, Noah Fleischmann, Nicolò Altamura, Edward Raff, James Holt, Kristopher Micinski