default search action
Dirk Husmeier
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j44]Yalei Yang, Dirk Husmeier, Hao Gao, Colin Berry, David Carrick, Aleksandra Radjenovic:
Automatic detection of myocardial ischaemia using generalisable spatio-temporal hierarchical Bayesian modelling of DCE-MRI. Comput. Medical Imaging Graph. 113: 102333 (2024) - [j43]Jianmei Zhou, Dirk Husmeier, Hao Gao, Changchun Yin, Changkai Qiu, Xu Jing, Yanfu Qi, Wentao Liu:
Bayesian Inversion of Frequency-Domain Airborne EM Data With Spatial Correlation Prior Information. IEEE Trans. Geosci. Remote. Sens. 62: 1-16 (2024) - [c29]David Dalton, Dirk Husmeier, Hao Gao:
Physics and Lie symmetry informed Gaussian processes. ICML 2024 - 2023
- [j42]Arash Rabbani, Hao Gao, Alan Lazarus, David Dalton, Yuzhang Ge, Kenneth Mangion, Colin Berry, Dirk Husmeier:
Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications. Comput. Medical Imaging Graph. 106: 102203 (2023) - [j41]William T. Harvey, Vinny Davies, Rodney S. Daniels, Lynne Whittaker, Victoria Gregory, Alan J. Hay, Dirk Husmeier, John W. McCauley, Richard E. Reeve:
A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses. PLoS Comput. Biol. 19(3) (2023) - [j40]Ionut Paun, Dirk Husmeier, Colin J. Torney:
Stochastic variational inference for scalable non-stationary Gaussian process regression. Stat. Comput. 33(2): 44 (2023) - [c28]Athanasios Tragakis, Chaitanya Kaul, Roderick Murray-Smith, Dirk Husmeier:
The Fully Convolutional Transformer for Medical Image Segmentation. WACV 2023: 3649-3658 - 2022
- [j39]Shaykhah Aldossari, Dirk Husmeier, Jason Matthiopoulos:
Transferable species distribution modelling: Comparative performance of Generalised Functional Response models. Ecol. Informatics 71: 101803 (2022) - [j38]Luiza Mihaela Paun, Dirk Husmeier:
Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models. Stat. Comput. 32(1): 1 (2022) - [i3]Athanasios Tragakis, Chaitanya Kaul, Roderick Murray-Smith, Dirk Husmeier:
The Fully Convolutional Transformer for Medical Image Segmentation. CoRR abs/2206.00566 (2022) - [i2]Arash Rabbani, Hao Gao, Dirk Husmeier:
Temporal extrapolation of heart wall segmentation in cardiac magnetic resonance images via pixel tracking. CoRR abs/2208.00165 (2022) - 2021
- [j37]Lukasz Romaszko, Agnieszka Borowska, Alan Lazarus, David Dalton, Colin Berry, Xiaoyu Luo, Dirk Husmeier, Hao Gao:
Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics. Artif. Intell. Medicine 119: 102140 (2021) - [j36]Mu Niu, Joe Wandy, Rónán Daly, Simon Rogers, Dirk Husmeier:
R package for statistical inference in dynamical systems using kernel based gradient matching: KGode. Comput. Stat. 36(1): 715-747 (2021) - [j35]Agnieszka Borowska, Diana Giurghita, Dirk Husmeier:
Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis. J. Comput. Phys. 429: 109999 (2021)
2010 – 2019
- 2019
- [j34]Benn Macdonald, Dirk Husmeier:
Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching. Stat. Comput. 29(5): 853-867 (2019) - 2018
- [j33]Joe Wandy, Mu Niu, Diana Giurghita, Rónán Daly, Simon Rogers, Dirk Husmeier:
ShinyKGode: an interactive application for ODE parameter inference using gradient matching. Bioinform. 34(13): 2314-2315 (2018) - [j32]Mu Niu, Benn Macdonald, Simon Rogers, Maurizio Filippone, Dirk Husmeier:
Statistical inference in mechanistic models: time warping for improved gradient matching. Comput. Stat. 33(2): 1091-1123 (2018) - [c27]Alan Lazarus, Dirk Husmeier, Theodore Papamarkou:
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations. AISTATS 2018: 1252-1260 - [i1]Umberto Noè, Dirk Husmeier:
On a New Improvement-Based Acquisition Function for Bayesian Optimization. CoRR abs/1808.06918 (2018) - 2017
- [j31]Marco Grzegorczyk, Andrej Aderhold, Dirk Husmeier:
Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration. Comput. Stat. 32(2): 717-761 (2017) - [j30]Vinny Davies, Richard E. Reeve, William T. Harvey, Francois F. Maree, Dirk Husmeier:
A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution. Comput. Stat. 32(3): 803-843 (2017) - [j29]Andrej Aderhold, Dirk Husmeier, Marco Grzegorczyk:
Approximate Bayesian inference in semi-mechanistic models. Stat. Comput. 27(4): 1003-1040 (2017) - 2016
- [c26]Mu Niu, Simon Rogers, Maurizio Filippone, Dirk Husmeier:
Parameter Inference in Differential Equation Models of Biopathways Using Time Warped Gradient Matching. CIBB 2016: 145-159 - [c25]Umberto Noè, Weiwei Chen, Maurizio Filippone, Nicholas Hill, Dirk Husmeier:
Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation Using Statistical Emulation. CIBB 2016: 184-198 - [c24]Mu Niu, Simon Rogers, Maurizio Filippone, Dirk Husmeier:
Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching. ICML 2016: 1699-1707 - 2015
- [c23]Vinny Davies, Richard E. Reeve, William T. Harvey, Dirk Husmeier:
Selecting Random Effect Components in a Sparse Hierarchical Bayesian Model for Identifying Antigenic Variability. CIBB 2015: 14-27 - [c22]Benn Macdonald, Catherine F. Higham, Dirk Husmeier:
Controversy in mechanistic modelling with Gaussian processes. ICML 2015: 1539-1547 - [c21]Benn Macdonald, Dirk Husmeier:
Computational Inference in Systems Biology. IWBBIO (2) 2015: 276-288 - [c20]Catherine F. Higham, Dirk Husmeier:
Inference of Circadian Regulatory Pathways Based on Delay Differential Equations. IWBBIO (2) 2015: 468-478 - 2014
- [c19]Vinny Davies, Richard E. Reeve, William T. Harvey, Francois F. Maree, Dirk Husmeier:
Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus. AISTATS 2014: 149-158 - [c18]Marco Grzegorczyk, Andrej Aderhold, V. Anne Smith, Dirk Husmeier:
Inference of Circadian Regulatory Networks. IWBBIO 2014: 1001-1014 - 2013
- [j28]Catherine F. Higham, Dirk Husmeier:
A Bayesian approach for parameter estimation in the extended clock gene circuit of Arabidopsis thaliana. BMC Bioinform. 14(S-10): S3 (2013) - [j27]Frank Dondelinger, Sophie Lèbre, Dirk Husmeier:
Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure. Mach. Learn. 90(2): 191-230 (2013) - [j26]Marco Grzegorczyk, Dirk Husmeier:
Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models. Mach. Learn. 91(1): 105-154 (2013) - [c17]Andrej Aderhold, Dirk Husmeier, V. Anne Smith:
Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes. AISTATS 2013: 75-84 - [c16]Frank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone:
ODE parameter inference using adaptive gradient matching with Gaussian processes. AISTATS 2013: 216-228 - 2012
- [j25]Andrej Aderhold, Dirk Husmeier, Jack J. Lennon, Colin M. Beale, V. Anne Smith:
Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data. Ecol. Informatics 11: 55-64 (2012) - [c15]Marco Grzegorczyk, Dirk Husmeier:
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters. AISTATS 2012: 467-476 - 2011
- [j24]Marco Grzegorczyk, Dirk Husmeier:
Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes. Bioinform. 27(5): 693-699 (2011) - [j23]Marco Grzegorczyk, Dirk Husmeier, Jörg Rahnenführer:
Modelling non-stationary dynamic gene regulatory processes with the BGM model. Comput. Stat. 26(2): 199-218 (2011) - [j22]Marco Grzegorczyk, Dirk Husmeier:
Non-homogeneous dynamic Bayesian networks for continuous data. Mach. Learn. 83(3): 355-419 (2011) - 2010
- [j21]Marco Grzegorczyk, Dirk Husmeier, Jörg Rahnenführer:
Modelling Nonstationary Gene Regulatory Processes. Adv. Bioinformatics 2010: 749848:1-749848:17 (2010) - [j20]Ali Faisal, Frank Dondelinger, Dirk Husmeier, Colin M. Beale:
Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods. Ecol. Informatics 5(6): 451-464 (2010) - [c14]Frank Dondelinger, Sophie Lèbre, Dirk Husmeier:
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing. ICML 2010: 303-310 - [c13]Dirk Husmeier, Frank Dondelinger, Sophie Lèbre:
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks. NIPS 2010: 901-909 - [p2]Kuang Lin, Dirk Husmeier:
Mixtures of Factor Analyzers for Modeling Transcriptional Regulation. Learning and Inference in Computational Systems Biology 2010: 153-200
2000 – 2009
- 2009
- [j19]Iain Milne, Dominik Lindner, Micha Bayer, Dirk Husmeier, Gráinne McGuire, David F. Marshall, Frank Wright:
TOPALi v2: a rich graphical interface for evolutionary analyses of multiple alignments on HPC clusters and multi-core desktops. Bioinform. 25(1): 126-127 (2009) - [j18]Kuang Lin, Dirk Husmeier:
Modelling Transcriptional Regulation with a Mixture of Factor Analyzers and Variational Bayesian Expectation Maximization. EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [c12]Marco Grzegorczyk, Dirk Husmeier:
Non-stationary continuous dynamic Bayesian networks. NIPS 2009: 682-690 - [c11]Marco Grzegorczyk, Dirk Husmeier:
Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. PRIB 2009: 113-124 - [c10]Alexander V. Mantzaris, Dirk Husmeier:
Distinguishing Regional from Within-Codon Rate Heterogeneity in DNA Sequence Alignments. PRIB 2009: 187-198 - 2008
- [j17]Marco Grzegorczyk, Dirk Husmeier, Kieron D. Edwards, Peter Ghazal, Andrew J. Millar:
Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. Bioinform. 24(18): 2071-2078 (2008) - [j16]Adriano Velasque Werhli, Dirk Husmeier:
Gene Regulatory Network Reconstruction by Bayesian Integration of Prior Knowledge and/or Different Experimental Conditions. J. Bioinform. Comput. Biol. 6(3): 543-572 (2008) - [j15]Marco Grzegorczyk, Dirk Husmeier:
Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. Mach. Learn. 71(2-3): 265-305 (2008) - 2006
- [j14]Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams:
A regularized discriminative model for the prediction of protein-peptide interactions. Bioinform. 22(5): 532-540 (2006) - [j13]Adriano Velasque Werhli, Marco Grzegorczyk, Dirk Husmeier:
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. Bioinform. 22(20): 2523-2531 (2006) - 2005
- [j12]Dirk Husmeier, Frank Wright, Iain Milne:
Detecting interspecific recombination with a pruned probabilistic divergence measure. Bioinform. 21(9): 1797-1806 (2005) - [c9]Dirk Husmeier:
Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models. ECCB/JBI 2005: 172 - [c8]Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams:
Probabilistic in Silico Prediction of Protein-Peptide Interactions. Systems Biology and Regulatory Genomics 2005: 188-197 - 2004
- [j11]Iain Milne, Frank Wright, Glenn Rowe, David F. Marshall, Dirk Husmeier, Gráinne McGuire:
TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments. Bioinform. 20(11): 1806-1807 (2004) - 2003
- [j10]Dirk Husmeier:
Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. Bioinform. 19(17): 2271-2282 (2003) - 2002
- [j9]Dirk Husmeier, Frank Wright:
A Bayesian approach to discriminate between alternative DNA sequence segmentations. Bioinform. 18(2): 226-234 (2002) - [j8]Dirk Husmeier, Frank Wright:
Detection of Recombination in DNA Multiple Alignments with Hidden Markov Models. J. Comput. Biol. 8(4): 401-427 (2002) - [c7]Dirk Husmeier, Gráinne McGuire:
Detecting recombination with MCMC. ISMB 2002: 345-353 - 2001
- [j7]Kaspar Althoefer, Bart Krekelberg, Dirk Husmeier, Lakmal D. Seneviratne:
Reinforcement learning in a rule-based navigator for robotic manipulators. Neurocomputing 37(1-4): 51-70 (2001) - [c6]Dirk Husmeier, Frank Wright:
Approximate Bayesian Discrimination between Alternative DNA Mosaic Structures. German Conference on Bioinformatics 2001: 182-184 - [c5]Dirk Husmeier, Frank Wright:
Probabilistic divergence measures for detecting interspecies recombination. ISMB (Supplement of Bioinformatics) 2001: 123-131 - 2000
- [j6]Dirk Husmeier:
The Bayesian Evidence Scheme for Regularizing Probability-Density Estimating Neural Networks. Neural Comput. 12(11): 2685-2717 (2000) - [j5]Dirk Husmeier:
Learning non-stationary conditional probability distributions. Neural Networks 13(3): 287-290 (2000) - [c4]Dirk Husmeier, Frank Wright:
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models. German Conference on Bioinformatics 2000: 19-26 - [p1]William D. Penny, Dirk Husmeier, Stephen J. Roberts:
The Bayesian Paradigm: Second Generation Neural Computing. Artificial Neural Networks in Biomedicine 2000: 11-23
1990 – 1999
- 1999
- [b1]Dirk Husmeier:
Neural networks for conditional probability estimation - forecasting beyond point predictions. Perspectives in neural computing, Springer 1999, ISBN 978-1-85233-095-8, pp. I-XXIII, 1-275 - [j4]Dirk Husmeier, William D. Penny, Stephen J. Roberts:
An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. Neural Networks 12(4-5): 677-705 (1999) - [c3]Dirk Husmeier, Gillian S. Patton, Myra O. McClure, John R. W. Harris, Stephen J. Roberts:
Neural networks for predicting Kaposi's sarcoma. IJCNN 1999: 3707-3711 - 1998
- [j3]Dirk Husmeier, John G. Taylor:
Neural Networks for Predicting Conditional Probability Densities: Improved Training Scheme Combining EM and RVFL. Neural Networks 11(1): 89-116 (1998) - [j2]Stephen J. Roberts, Dirk Husmeier, Iead Rezek, William D. Penny:
Bayesian Approaches to Gaussian Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 20(11): 1133-1142 (1998) - 1997
- [j1]Dirk Husmeier, John G. Taylor:
Predicting Conditional Probability Densities of Stationary Stochastic Time Series. Neural Networks 10(3): 479-497 (1997) - [c2]Dirk Husmeier, John G. Taylor:
Modeling Conditional Probabilities with Committees of RVFL Networks. ICANN 1997: 1053-1058 - [c1]Dirk Husmeier, John G. Taylor:
Predicting Conditional Probability Densities with the Gaussian Mixture - RVFL Network. ICANNGA 1997: 477-481
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:14 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint