Tom Heskes

Orcid: 0000-0002-3398-5235

Affiliations:
  • Radboud University Nijmegen, NL


According to our database1, Tom Heskes authored at least 187 papers between 1992 and 2025.

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

Timeline

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Bibliography

2025
Invariant neural architecture for learning term synthesis in instantiation proving.
J. Symb. Comput., 2025

2024
How to evaluate uncertainty estimates in machine learning for regression?
Neural Networks, 2024

Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?
J. Mach. Learn. Res., 2024

Optimal training of Mean Variance Estimation neural networks.
Neurocomputing, 2024

Composite Quantile Regression With XGBoost Using the Novel Arctan Pinball Loss.
CoRR, 2024

Acquiring Better Load Estimates by Combining Anomaly and Change-point Detection in Power Grid Time-series Measurements.
CoRR, 2024

Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities.
CoRR, 2024

2023
Automatic Inference of Fault Tree Models Via Multi-Objective Evolutionary Algorithms.
IEEE Trans. Dependable Secur. Comput., 2023

Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison.
CoRR, 2023

Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid.
CoRR, 2023

Likelihood-ratio-based confidence intervals for neural networks.
CoRR, 2023

Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022
Machine Learning Meets The Herbrand Universe.
CoRR, 2022

Confident Neural Network Regression with Bootstrapped Deep Ensembles.
CoRR, 2022

Non-parametric synergy modeling of chemical compounds with Gaussian processes.
BMC Bioinform., 2022

Guiding an Automated Theorem Prover with Neural Rewriting.
Proceedings of the Automated Reasoning - 11th International Joint Conference, 2022

2021
Probabilistic Modelling of Gait for Robust Passive Monitoring in Daily Life.
IEEE J. Biomed. Health Informatics, 2021

Spectral Ranking of Causal Influence in Complex Systems.
Entropy, 2021

Going Grayscale: The Road to Understanding and Improving Unlearnable Examples.
CoRR, 2021

Swift sky localization of gravitational waves using deep learning seeded importance sampling.
CoRR, 2021

Learning Equational Theorem Proving.
CoRR, 2021

2020
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Discovering cause-effect relationships in spatial systems with a known direction based on observational data.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Stable Specification Search in Structural Equation Models with Latent Variables.
ACM Trans. Intell. Syst. Technol., 2019

Learning causal structure from mixed data with missing values using Gaussian copula models.
Stat. Comput., 2019

A novel Bayesian approach for latent variable modeling from mixed data with missing values.
Stat. Comput., 2019

Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies.
PLoS Comput. Biol., 2019

Large-scale local causal inference of gene regulatory relationships.
Int. J. Approx. Reason., 2019

Constraining the Parameters of High-Dimensional Models with Active Learning.
CoRR, 2019

2018
A scalable preference model for autonomous decision-making.
Mach. Learn., 2018

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

Bigger Buffer k-d Trees on Multi-Many-Core Systems.
Proceedings of the High Performance Computing for Computational Science - VECPAR 2018, 2018

Learning the Causal Structure of Copula Models with Latent Variables.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 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 Process. Lett., 2017

Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD.
Int. J. Data Sci. Anal., 2017

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

RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets.
Bioinform., 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 Syst. Biol., 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, 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

Exploring Constraint: Simulating Self-Organization and Autogenesis in the Autogenic Automaton.
Proceedings of the Fifteenth International Conference on the Simulation and Synthesis of Living Systems, 2016

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

MAGMA: Generalized Gene-Set Analysis of GWAS Data.
PLoS Comput. Biol., 2015

Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates.
PLoS Comput. Biol., 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. Reason., 2014

Gaussian mixture models and semantic gating improve reconstructions from human brain activity.
Frontiers Comput. Neurosci., 2014

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

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

A comparative study of cell classifiers for image-based high-throughput screening.
BMC Bioinform., 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 15th Annual Conference of the International Speech Communication Association, 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 Comput., 2013

Efficiently learning the preferences of people.
Mach. Learn., 2013

Semi-supervised Ranking Pursuit.
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 Comput. Biol., 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. Speech Audio Process., 2011

Dynamic decoding of ongoing perception.
NeuroImage, 2011

Approximate Marginals in Latent Gaussian Models.
J. Mach. Learn. Res., 2011

Properties of Bethe Free Energies and Message Passing in Gaussian Models.
J. Artif. Intell. Res., 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 19th European Symposium on Artificial Neural Networks, 2011

A structure independent algorithm for causal discovery.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 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 Comput., 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 <i>Plasmodium falciparum</i>.
Bioinform., 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 17th European Symposium on Artificial Neural Networks, 2009

Exploring the impact of alternative feature representations on BCI classification.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 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.
Comput. Stat. Data Anal., 2007

Predicting carcinoid heart disease with the noisy-threshold classifier.
Artif. Intell. 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.
Stat. Comput., 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.
J. Mach. Learn. Res., 2005

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

Exploring the Noisy Threshold Function in Designing Bayesian Networks.
Proceedings of the Research and Development in Intelligent Systems XXII, 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 Comput., 2004

Novel approximations for inference and learning in nonlinear dynamical systems.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 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 Comput. Appl., 2003

Task Clustering and Gating for Bayesian Multitask Learning.
J. Mach. Learn. Res., 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 Comput., 2000

Input selection based on an ensemble.
Neurocomputing, 2000

EM Algorithms for Self-Organizing Maps.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 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

Survival Analysis: A Neural-Bayesian Approach.
Proceedings of the Artificial Neural Networks in Medicine and Biology, 2000

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

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

Model clustering by deterministic annealing.
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

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

How Dependencies between Successive Examples Affect On-Line Learning.
Neural Comput., 1996

Transition times in self-organizing maps.
Biol. Cybern., 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

1995
Output Coding and Modularity for Multi-Class Problems.
Proceedings of the Neural Networks: Artificial Intelligence and Industrial Applications, 1995

A Neural Model of Visual Attention.
Proceedings of the Neural Networks: Artificial Intelligence and Industrial Applications, 1995

1994
Stochastics of on-line back-propagation.
Proceedings of the 2nd European Symposium on Artificial Neural Networks, 1994

1993
Error potentials for self-organization.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

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


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