Dirk Husmeier
Orcid: 0000-0003-1673-7413
According to our database1,
Dirk Husmeier
authored at least 79 papers
between 1997 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
2000
2005
2010
2015
2020
2025
0
1
2
3
4
5
6
1
1
1
2
3
3
3
1
3
3
3
1
3
2
2
3
2
1
1
1
2
1
2
1
2
1
1
1
1
3
4
2
2
1
2
3
2
1
2
1
1
2
1
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2025
Advanced statistical inference of myocardial stiffness: A time series Gaussian process approach of emulating cardiac mechanics for real-time clinical decision support.
Comput. Biol. Medicine, 2025
2024
Bayesian Inversion of Frequency-Domain Airborne EM Data With Spatial Correlation Prior Information.
IEEE Trans. Geosci. Remote. Sens., 2024
Automatic detection of myocardial ischaemia using generalisable spatio-temporal hierarchical Bayesian modelling of DCE-MRI.
Comput. Medical Imaging Graph., 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications.
Comput. Medical Imaging Graph., June, 2023
Stochastic variational inference for scalable non-stationary Gaussian process regression.
Stat. Comput., April, 2023
A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses.
PLoS Comput. Biol., March, 2023
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
2022
Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models.
Stat. Comput., 2022
Transferable species distribution modelling: Comparative performance of Generalised Functional Response models.
Ecol. Informatics, 2022
Temporal extrapolation of heart wall segmentation in cardiac magnetic resonance images via pixel tracking.
CoRR, 2022
2021
Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis.
J. Comput. Phys., 2021
R package for statistical inference in dynamical systems using kernel based gradient matching: KGode.
Comput. Stat., 2021
Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics.
Artif. Intell. Medicine, 2021
2019
Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching.
Stat. Comput., 2019
2018
Statistical inference in mechanistic models: time warping for improved gradient matching.
Comput. Stat., 2018
CoRR, 2018
ShinyKGode: an interactive application for ODE parameter inference using gradient matching.
Bioinform., 2018
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Comput. Stat., 2017
A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution.
Comput. Stat., 2017
2016
Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation Using Statistical Emulation.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2016
Parameter Inference in Differential Equation Models of Biopathways Using Time Warped Gradient Matching.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2016
2015
Proceedings of the Bioinformatics and Biomedical Engineering, 2015
Proceedings of the Bioinformatics and Biomedical Engineering, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
Selecting Random Effect Components in a Sparse Hierarchical Bayesian Model for Identifying Antigenic Variability.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2015
2014
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014
Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
2013
Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models.
Mach. Learn., 2013
Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure.
Mach. Learn., 2013
A Bayesian approach for parameter estimation in the extended clock gene circuit of Arabidopsis thaliana.
BMC Bioinform., 2013
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013
Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013
2012
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data.
Ecol. Informatics, 2012
2011
Comput. Stat., 2011
Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes.
Bioinform., 2011
2010
Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods.
Ecol. Informatics, 2010
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Mixtures of Factor Analyzers for Modeling Transcriptional Regulation.
Proceedings of the Learning and Inference in Computational Systems Biology., 2010
2009
Modelling Transcriptional Regulation with a Mixture of Factor Analyzers and Variational Bayesian Expectation Maximization.
EURASIP J. Bioinform. Syst. Biol., 2009
TOPALi v2: a rich graphical interface for evolutionary analyses of multiple alignments on HPC clusters and multi-core desktops.
Bioinform., 2009
Distinguishing Regional from Within-Codon Rate Heterogeneity in DNA Sequence Alignments.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks.
Proceedings of the Pattern Recognition in Bioinformatics, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
2008
Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move.
Mach. Learn., 2008
Gene Regulatory Network Reconstruction by Bayesian Integration of Prior Knowledge and/or Different Experimental Conditions.
J. Bioinform. Comput. Biol., 2008
Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler.
Bioinform., 2008
2006
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.
Bioinform., 2006
A regularized discriminative model for the prediction of protein-peptide interactions.
Bioinform., 2006
2005
Detecting interspecific recombination with a pruned probabilistic divergence measure.
Bioinform., 2005
Proceedings of the Systems Biology and Regulatory Genomics, 2005
Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models.
Proceedings of the ECCB/JBI'05 Proceedings, Fourth European Conference on Computational Biology/Sixth Meeting of the Spanish Bioinformatics Network (Jornadas de BioInformática), Palacio de Congresos, Madrid, Spain, September 28, 2005
2004
TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments.
Bioinform., 2004
2003
Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks.
Bioinform., 2003
2002
J. Comput. Biol., 2002
Bioinform., 2002
Detecting recombination with MCMC.
Proceedings of the Tenth International Conference on Intelligent Systems for Molecular Biology, 2002
2001
Neurocomputing, 2001
Probabilistic divergence measures for detecting interspecies recombination.
Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001
Approximate Bayesian Discrimination between Alternative DNA Mosaic Structures.
Proceedings of the Computer science and biology: Proceedings of the German Conference on Bioinformatics, 2001
2000
The Bayesian Evidence Scheme for Regularizing Probability-Density Estimating Neural Networks.
Neural Comput., 2000
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models.
Proceedings of the German Conference on Bioinformatics (GCB 2000), 2000
Proceedings of the Artificial Neural Networks in Biomedicine, 2000
1999
An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers.
Neural Networks, 1999
Proceedings of the International Joint Conference Neural Networks, 1999
Neural networks for conditional probability estimation - forecasting beyond point predictions.
Perspectives in neural computing, Springer, ISBN: 978-1-85233-095-8, 1999
1998
IEEE Trans. Pattern Anal. Mach. Intell., 1998
Neural Networks for Predicting Conditional Probability Densities: Improved Training Scheme Combining EM and RVFL.
Neural Networks, 1998
1997
Neural Networks, 1997
Predicting Conditional Probability Densities with the Gaussian Mixture - RVFL Network.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1997
Proceedings of the Artificial Neural Networks, 1997