Tom Heskes

According to our database1, Tom Heskes authored at least 164 papers between 1992 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2018
A scalable preference model for autonomous decision-making.
Machine Learning, 2018

The stablespec package for causal discovery on cross-sectional and longitudinal data in R.
Neurocomputing, 2018

A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks.
CoRR, 2018

A Novel Bayesian Approach for Latent Variable Modeling from Mixed Data with Missing Values.
CoRR, 2018

Stable specification search in structural equation model with latent variables.
CoRR, 2018

Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates.
Bioinformatics, 2018

A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017
Expectation Propagation.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Multi-Domain Transfer Component Analysis for Domain Generalization.
Neural Processing Letters, 2017

Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD.
I. J. Data Science and Analytics, 2017

Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness.
CoRR, 2017

Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers.
BMC Bioinformatics, 2017

RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets.
Bioinformatics, 2017

Causality on cross-sectional data: Stable specification search in constrained structural equation modeling.
Appl. Soft Comput., 2017

Massively-parallel best subset selection for ordinary least-squares regression.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Robust Estimation of Gaussian Copula Causal Structure from Mixed Data with Missing Values.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling.
CoRR, 2016

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.
CoRR, 2016

Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin.
CoRR, 2016

The Artificial Mind's Eye: Resisting Adversarials for Convolutional Neural Networks using Internal Projection.
CoRR, 2016

BCM: toolkit for Bayesian analysis of Computational Models using samplers.
BMC Systems Biology, 2016

Copula PC Algorithm for Causal Discovery from Mixed Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Computing Lower and Upper Bounds on the Probability of Causal Statements.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

Causal Discovery from Big Data - Mission (Im)possible?.
Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART 2016), 2016

2015
A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions.
IEEE/ACM Trans. Comput. Biology Bioinform., 2015

MAGMA: Generalized Gene-Set Analysis of GWAS Data.
PLoS Computational Biology, 2015

Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates.
PLoS Computational Biology, 2015

Gaussian mixture models and semantic gating improve reconstructions from human brain activity.
Front. Comput. Neurosci., 2015

Causality on Cross-Sectional Data: Stable Specification Search in Constrained Structural Equation Modeling.
CoRR, 2015

Bigger Buffer k-d Trees on Multi-Many-Core Systems.
CoRR, 2015

Hidden Markov Models for Reading Words from the Human Brain.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling.
Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, 2015

Small white matter lesion detection in cerebral small vessel disease.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Domain Generalization Based on Transfer Component Analysis.
Proceedings of the Advances in Computational Intelligence, 2015

Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

KeCo: Kernel-Based Online Co-agreement Algorithm.
Proceedings of the Discovery Science - 18th International Conference, 2015

Causal Discovery from Medical Data: Dealing with Missing Values and a Mixture of Discrete and Continuous Data.
Proceedings of the Artificial Intelligence in Medicine, 2015

2014
Structurally-informed Bayesian functional connectivity analysis.
NeuroImage, 2014

Premise Selection for Mathematics by Corpus Analysis and Kernel Methods.
J. Autom. Reasoning, 2014

Quantifying uncertainty in brain network measures using Bayesian connectomics.
Front. Comput. Neurosci., 2014

Properties of Bethe Free Energies and Message Passing in Gaussian Models.
CoRR, 2014

A fast algorithm for determining bounds and accurate approximate p-values of the rank product statistic for replicate experiments.
BMC Bioinformatics, 2014

A comparative study of cell classifiers for image-based high-throughput screening.
BMC Bioinformatics, 2014

Gaussian mixture models improve fMRI-based image reconstruction.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Using Topology Information for Protein-Protein Interaction Prediction.
Proceedings of the Pattern Recognition in Bioinformatics, 2014

Causal Discovery from Databases with Discrete and Continuous Variables.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Speaker diarization using gesture and speech.
Proceedings of the INTERSPEECH 2014, 2014

Mutual Information Estimation with Random Forests.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

Motion history images for online speaker/signer diarization.
Proceedings of the IEEE International Conference on Acoustics, 2014

Unsupervised Feature Learning for Visual Sign Language Identification.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

2013
Linear reconstruction of perceived images from human brain activity.
NeuroImage, 2013

Bayesian inference of structural brain networks.
NeuroImage, 2013

Bayesian Sparse Partial Least Squares.
Neural Computation, 2013

Efficiently learning the preferences of people.
Machine Learning, 2013

IPF for Discrete Chain Factor Graphs
CoRR, 2013

Expectation Propogation for approximate inference in dynamic Bayesian networks
CoRR, 2013

Semi-supervised Ranking Pursuit.
CoRR, 2013

Cyclic Causal Discovery from Continuous Equilibrium Data.
CoRR, 2013

Learning Sparse Causal Models is not NP-hard.
CoRR, 2013

Cyclic Causal Discovery from Continuous Equilibrium Data.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Learning Sparse Causal Models is not NP-hard.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data.
Proceedings of the Partially Supervised Learning - Second IAPR International Workshop, 2013

Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains.
Proceedings of the Multiple Classifier Systems, 11th International Workshop, 2013

Bayesian Probabilities for Constraint-Based Causal Discovery.
Proceedings of the IJCAI 2013, 2013

Automatic sign language identification.
Proceedings of the IEEE International Conference on Image Processing, 2013

The gesturer is the speaker.
Proceedings of the IEEE International Conference on Acoustics, 2013

Automatic Signer Diarization - The Mover Is the Signer Approach.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013

Improving Native Language Identification with TF-IDF Weighting.
Proceedings of the Eighth Workshop on Innovative Use of NLP for Building Educational Applications, 2013

2012
Molecular Machines in the Synapse: Overlapping Protein Sets Control Distinct Steps in Neurosecretion.
PLoS Computational Biology, 2012

Approximate Inference and Constrained Optimization
CoRR, 2012

A Bayesian Approach to Constraint Based Causal Inference
CoRR, 2012

Bounds on the Bethe Free Energy for Gaussian Networks
CoRR, 2012

A Logical Characterization of Constraint-Based Causal Discovery
CoRR, 2012

A Bayesian Approach to Constraint Based Causal Inference.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

A Linear Gaussian Framework for Decoding of Perceived Images.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Online Co-regularized Algorithms.
Proceedings of the Discovery Science - 15th International Conference, 2012

Overview and Evaluation of Premise Selection Techniques for Large Theory Mathematics.
Proceedings of the Automated Reasoning - 6th International Joint Conference, 2012

2011
Editorial: One Year as EiC, and Editorial-Board Changes at TNN.
IEEE Trans. Neural Networks, 2011

Predicting Preference Judgments of Individual Normal and Hearing-Impaired Listeners With Gaussian Processes.
IEEE Trans. Audio, Speech & Language Processing, 2011

Dynamic decoding of ongoing perception.
NeuroImage, 2011

Approximate Marginals in Latent Gaussian Models.
Journal of Machine Learning Research, 2011

Properties of Bethe Free Energies and Message Passing in Gaussian Models.
J. Artif. Intell. Res., 2011

Premise Selection for Mathematics by Corpus Analysis and Kernel Methods
CoRR, 2011

A Logical Characterization of Constraint-Based Causal Discovery.
Proceedings of the UAI 2011, 2011

Semantic Graph Kernels for Automated Reasoning.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

On Causal Discovery with Cyclic Additive Noise Models.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

The Dynamic Beamformer.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

Learning2Reason.
Proceedings of the Intelligent Computer Mathematics - 18th Symposium, 2011

Learning from Multiple Annotators with Gaussian Processes.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

A Markov Random Field Approach to Neural Encoding and Decoding.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Multi-output Ranking for Automated Reasoning.
Proceedings of the KDIR 2011, 2011

Learning of causal relations.
Proceedings of the ESANN 2011, 2011

A structure independent algorithm for causal discovery.
Proceedings of the ESANN 2011, 2011

2010
Expectation Propagation.
Proceedings of the Encyclopedia of Machine Learning, 2010

Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior.
NeuroImage, 2010

Neural Decoding with Hierarchical Generative Models.
Neural Computation, 2010

Improving posterior marginal approximations in latent Gaussian models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Multi-task preference learning with an application to hearing aid personalization.
Neurocomputing, 2010

Causal discovery in multiple models from different experiments.
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

Bayesian Monte Carlo for the Global Optimization of Expensive Functions.
Proceedings of the ECAI 2010, 2010

Co-Regularized Least-Squares for Label Ranking.
Proceedings of the Preference Learning., 2010

2009
Selecting features for BCI control based on a covert spatial attention paradigm.
Neural Networks, 2009

Interpreting single trial data using groupwise regularisation.
NeuroImage, 2009

Gene regulation in the intraerythrocytic cycle of Plasmodium falciparum.
Bioinformatics, 2009

Bayesian Source Localization with the Multivariate Laplace Prior.
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

Multi-task Preference learning with Gaussian Processes.
Proceedings of the ESANN 2009, 2009

Exploring the impact of alternative feature representations on BCI classification.
Proceedings of the ESANN 2009, 2009

2008
Bounds on the Bethe Free Energy for Gaussian Networks.
Proceedings of the UAI 2008, 2008

2007
Learning and approximate inference in dynamic hierarchical models.
Computational Statistics & Data Analysis, 2007

Predicting carcinoid heart disease with the noisy-threshold classifier.
Artificial Intelligence in Medicine, 2007

Expectation Propagation for Rating Players in Sports Competitions.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Deterministic approximate inference techniques for conditionally Gaussian state space models.
Statistics and Computing, 2006

Convexity Arguments for Efficient Minimization of the Bethe and Kikuchi Free Energies.
J. Artif. Intell. Res., 2006

Symmetric Causal Independence Models for Classification.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

EM Algorithm for Symmetric Causal Independence Models.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Change Point Problems in Linear Dynamical Systems.
Journal of Machine Learning Research, 2005

Novel approximations for inference in nonlinear dynamical systems using expectation propagation.
Neurocomputing, 2005

Gaussian Quadrature Based Expectation Propagation.
Proceedings of the BNAIC 2005, 2005

Use of the Noisy Threshold Function in Building Bayesian Networks.
Proceedings of the BNAIC 2005, 2005

Incremental Utility Elicitation for Adaptive Personalization.
Proceedings of the BNAIC 2005, 2005

Gaussian Quadrature Based Expectation Propagation.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
On the Uniqueness of Loopy Belief Propagation Fixed Points.
Neural Computation, 2004

Novel approximations for inference and learning in nonlinear dynamical systems.
Proceedings of the ESANN 2004, 2004

2003
Hierarchical Visualization of Time-Series Data Using Switching Linear Dynamical Systems.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Clustering ensembles of neural network models.
Neural Networks, 2003

Optimising newspaper sales using neural-Bayesian technology.
Neural Computing and Applications, 2003

Task Clustering and Gating for Bayesian Multitask Learning.
Journal of Machine Learning Research, 2003

Approximate Inference and Constrained Optimization.
Proceedings of the UAI '03, 2003

Iterated extended Kalman smoothing with expectation-propagation.
Proceedings of the NNSP 2003, 2003

Approximate Expectation Maximization.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Multi-scale Switching Linear Dynamical Systems.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

Generalized belief propagation for approximate inference in hybrid Bayesian networks.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002
Approximate algorithms for neural-Bayesian approaches.
Theor. Comput. Sci., 2002

IPF for Discrete Chain Factor Graphs.
Proceedings of the UAI '02, 2002

Expectation Propogation for Approximate Inference in Dynamic Bayesian Networks.
Proceedings of the UAI '02, 2002

Fractional Belief Propagation.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Stable Fixed Points of Loopy Belief Propagation Are Local Minima of the Bethe Free Energy.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models.
Proceedings of the WEBKDD 2002, 2002

Model Clustering for Neural Network Ensembles.
Proceedings of the Artificial Neural Networks, 2002

2001
Self-organizing maps, vector quantization, and mixture modeling.
IEEE Trans. Neural Networks, 2001

2000
On "Natural" Learning and Pruning in Multilayered Perceptrons.
Neural Computation, 2000

Input selection based on an ensemble.
Neurocomputing, 2000

EM Algorithms for Self-Organizing Maps.
IJCNN (6), 2000

General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of Distributions.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

Empirical Bayes for Learning to Learn.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999
Pruning Using Parameter and Neuronal Metrics.
Neural Computation, 1999

Partial Retraining: A New Approach to Input Relevance Determination.
Int. J. Neural Syst., 1999

Model clustering by deterministic annealing.
Proceedings of the ESANN 1999, 1999

1998
Bias/Variance Decompositions for Likelihood-Based Estimators.
Neural Computation, 1998

Solving a Huge Number of Similar Tasks: A Combination of Multi-Task Learning and a Hierarchical Bayesian Approach.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

1997
Task-Dependent Learning of Attention.
Neural Networks, 1997

Selecting Weighting Factors in Logarithmic Opinion Pools.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Input Selection with Partial Retraining.
Proceedings of the Artificial Neural Networks, 1997

1996
A theoretical comparison of batch-mode, on-line, cyclic, and almost-cyclic learning.
IEEE Trans. Neural Networks, 1996

Transition times in self-organizing maps.
Biological Cybernetics, 1996

Balancing Between Bagging and Bumping.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Practical Confidence and Prediction Intervals.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1994
Stochastics of on-line back-propagation.
Proceedings of the ESANN 1994, 1994

1992
Retrieval of pattern sequences at variable speeds in a neural network with delays.
Neural Networks, 1992


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