Tom Heskes

ORCID

Publication Activity (10 Years)

Years Active: 1992-2023
Publications (10 Years): 70

Top Venues

Publications

Lisandro Arturo Jimenez-Roa, Tom Heskes, Tiedo Tinga, Mariëlle Stoelinga
Automatic Inference of Fault Tree Models Via Multi-Objective Evolutionary Algorithms. IEEE Trans. Dependable Secur. Comput. 20 (4) (2023)
Mirthe Maria Van Diepen, Ioan Gabriel Bucur, Tom Heskes, Tom Claassen
Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding. CLeaR (2023)
Charlotte Cambier van Nooten, Tom van de Poll, Sonja Füllhase, Jacco Heres, Tom Heskes, Yuliya Shapovalova
Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid. CoRR (2023)
Roel Bouman, Zaharah Bukhsh, Tom Heskes
Unsupervised anomaly detection algorithms on real-world data: how many do we need? CoRR (2023)
Lisandro Arturo Jimenez-Roa, Tom Heskes, Mariëlle Stoelinga
Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison. CoRR (2023)
Laurens Sluijterman, Eric Cator, Tom Heskes
Likelihood-ratio-based confidence intervals for neural networks. CoRR (2023)
Laurens Sluijterman, Eric Cator, Tom Heskes
Optimal Training of Mean Variance Estimation Neural Networks. CoRR (2023)
Lisandro Arturo Jimenez-Roa, Tom Heskes, Tiedo Tinga, Mariëlle Stoelinga
Automatic inference of fault tree models via multi-objective evolutionary algorithms. CoRR (2022)
Laurens Sluijterman, Eric Cator, Tom Heskes
Confident Neural Network Regression with Bootstrapped Deep Ensembles. CoRR (2022)
Yuliya Shapovalova, Tom Heskes, Tjeerd Dijkstra
Non-parametric synergy modeling of chemical compounds with Gaussian processes. BMC Bioinform. 23 (1) (2022)
Jelle Piepenbrock, Tom Heskes, Mikolás Janota, Josef Urban
Guiding an Automated Theorem Prover with Neural Rewriting. IJCAR (2022)
Jelle Piepenbrock, Josef Urban, Konstantin Korovin, Miroslav Olsák, Tom Heskes, Mikolas Janota
Machine Learning Meets The Herbrand Universe. CoRR (2022)
Laurens Sluijterman, Eric Cator, Tom Heskes
How to Evaluate Uncertainty Estimates in Machine Learning for Regression? CoRR (2021)
Errol Zalmijn, Tom Heskes, Tom Claassen
Spectral Ranking of Causal Influence in Complex Systems. Entropy 23 (3) (2021)
Jelle Piepenbrock, Tom Heskes, Mikolás Janota, Josef Urban
Learning Equational Theorem Proving. CoRR (2021)
Zhuoran Liu, Zhengyu Zhao, Alex Kolmus, Tijn Berns, Twan van Laarhoven, Tom Heskes, Martha A. Larson
Going Grayscale: The Road to Understanding and Improving Unlearnable Examples. CoRR (2021)
Alex Kolmus, Grégory Baltus, Justin Janquart, Twan van Laarhoven, Sarah Caudill, Tom Heskes
Swift sky localization of gravitational waves using deep learning seeded importance sampling. CoRR (2021)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models. UAI (2020)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models. CoRR (2020)
Tom Heskes, Evi Sijben, Ioan Gabriel Bucur, Tom Claassen
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models. CoRR (2020)
Errol Zalmijn, Tom Heskes, Tom Claassen
Spectral Ranking of Causal Influence in Complex Systems. CoRR (2020)
Tom Heskes, Evi Sijben, Ioan Gabriel Bucur, Tom Claassen
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models. NeurIPS (2020)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
Large-scale local causal inference of gene regulatory relationships. Int. J. Approx. Reason. 115 (2019)
Ruifei Cui, Ioan Gabriel Bucur, Perry Groot, Tom Heskes
A novel Bayesian approach for latent variable modeling from mixed data with missing values. Stat. Comput. 29 (5) (2019)
Sascha Caron, Tom Heskes, Sydney Otten, Bob Stienen
Constraining the Parameters of High-Dimensional Models with Active Learning. CoRR (2019)
Payam Piray, Amir Dezfouli, Tom Heskes, Michael J. Frank, Nathaniel D. Daw
Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies. PLoS Comput. Biol. 15 (6) (2019)
Ridho Rahmadi, Perry Groot, Tom Heskes
Stable Specification Search in Structural Equation Models with Latent Variables. ACM Trans. Intell. Syst. Technol. 10 (5) (2019)
Ruifei Cui, Perry Groot, Tom Heskes
Learning causal structure from mixed data with missing values using Gaussian copula models. Stat. Comput. 29 (2) (2019)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
Large-Scale Local Causal Inference of Gene Regulatory Relationships. CoRR (2019)
Bram Thijssen, Tjeerd Dijkstra, Tom Heskes, Lodewyk F. A. Wessels
Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates. Bioinform. 34 (5) (2018)
Markus Peters, Maytal Saar-Tsechansky, Wolfgang Ketter, Sinead A. Williamson, Perry Groot, Tom Heskes
A scalable preference model for autonomous decision-making. Mach. Learn. 107 (6) (2018)
Ioan Gabriel Bucur, Tom van Bussel, Tom Claassen, Tom Heskes
A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks. PGM (2018)
Ruifei Cui, Ioan Gabriel Bucur, Perry Groot, Tom Heskes
A Novel Bayesian Approach for Latent Variable Modeling from Mixed Data with Missing Values. CoRR (2018)
Ruifei Cui, Perry Groot, Moritz Schauer, Tom Heskes
Learning the Causal Structure of Copula Models with Latent Variables. UAI (2018)
Ridho Rahmadi, Perry Groot, Tom Heskes
Stable specification search in structural equation model with latent variables. CoRR (2018)
Ioan Gabriel Bucur, Tom van Bussel, Tom Claassen, Tom Heskes
A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks. CoRR (2018)
Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes
Bigger Buffer k-d Trees on Multi-Many-Core Systems. VECPAR (2018)
Ridho Rahmadi, Perry Groot, Tom Heskes
The stablespec package for causal discovery on cross-sectional and longitudinal data in R. Neurocomputing 275 (2018)
Fabian Gieseke, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, Tom Heskes
Massively-parallel best subset selection for ordinary least-squares regression. SSCI (2017)
Ruifei Cui, Perry Groot, Tom Heskes
Robust Estimation of Gaussian Copula Causal Structure from Mixed Data with Missing Values. ICDM (2017)
Rob Eisinga, Tom Heskes, Ben Pelzer, Manfred te Grotenhuis
Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers. BMC Bioinform. 18 (1) (2017)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness. CoRR (2017)
Elena Sokolova, Daniel von Rhein, Jilly Naaijen, Perry Groot, Tom Claassen, Jan K. Buitelaar, Tom Heskes
Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD. Int. J. Data Sci. Anal. 3 (2) (2017)
Francesco Del Carratore, Andris Jankevics, Rob Eisinga, Tom Heskes, Fangxin Hong, Rainer Breitling
RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets. Bioinform. 33 (17) (2017)
Ridho Rahmadi, Perry Groot, Marianne Heins, Hans Knoop, Tom Heskes
Causality on cross-sectional data: Stable specification search in constrained structural equation modeling. Appl. Soft Comput. 52 (2017)
Thomas Grubinger, Adriana Birlutiu, Holger Schöner, Thomas Natschläger, Tom Heskes
Multi-Domain Transfer Component Analysis for Domain Generalization. Neural Process. Lett. 46 (3) (2017)
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness. AISTATS (2017)
Koen Vijverberg, Mohsen Ghafoorian, Inge W. M. van Uden, Frank-Erik de Leeuw, Bram Platel, Tom Heskes
A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation. Medical Imaging: Computer-Aided Diagnosis (2016)
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Inge van Uden, Clara I. Sánchez, Geert Litjens, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities. CoRR (2016)
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, I. W. M. van Uden, Frank-Erik de Leeuw, Elena Marchiori, Bram van Ginneken, Bram Platel
Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation. ISBI (2016)
Tom Heskes
Causal Discovery from Big Data - Mission (Im)possible?. ICAART (1) (2016)
Harm Berntsen, Wouter Kuijper, Tom Heskes
The Artificial Mind's Eye: Resisting Adversarials for Convolutional Neural Networks using Internal Projection. CoRR (2016)
Bram Thijssen, T. M. H. Dijkstra, Tom Heskes, Lodewyk F. A. Wessels
BCM: toolkit for Bayesian analysis of Computational Models using samplers. BMC Syst. Biol. 10 (2016)
Ruifei Cui, Perry Groot, Tom Heskes
Copula PC Algorithm for Causal Discovery from Mixed Data. ECML/PKDD (2) (2016)
Terrence W. Deacon, Tom Heskes, Stefan Leijnen
Exploring Constraint: Simulating Self-Organization and Autogenesis in the Autogenic Automaton. ALIFE (2016)
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Mayra Bergkamp, Joost Wissink, Jiri Obels, Karlijn Keizer, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin. CoRR (2016)
Ridho Rahmadi, Perry Groot, Marieke M. H. C. van Rijn, Jan A. J. G. van den Brand, Marianne Heins, Hans Knoop, Tom Heskes
Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling. CoRR (2016)
Elena Sokolova, Martine Hoogman, Perry Groot, Tom Claassen, Tom Heskes
Computing Lower and Upper Bounds on the Probability of Causal Statements. Probabilistic Graphical Models (2016)
Mohsen Ghafoorian, Nico Karssemeijer, Inge van Uden, Frank-Erik de Leeuw, Tom Heskes, Elena Marchiori, Bram Platel
Small white matter lesion detection in cerebral small vessel disease. Medical Imaging: Computer-Aided Diagnosis (2015)
Elena Sokolova, Perry Groot, Tom Claassen, Daniel von Rhein, Jan K. Buitelaar, Tom Heskes
Causal Discovery from Medical Data: Dealing with Missing Values and a Mixture of Discrete and Continuous Data. AIME (2015)
Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes
Bigger Buffer k-d Trees on Multi-Many-Core Systems. CoRR (2015)
Ridho Rahmadi, Perry Groot, Marianne Heins, Hans Knoop, Tom Heskes
Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling. AALTD@PKDD/ECML (2015)
Ridho Rahmadi, Perry Groot, Marianne Heins, Hans Knoop, Tom Heskes
Causality on Cross-Sectional Data: Stable Specification Search in Constrained Structural Equation Modeling. CoRR (2015)
Laurens Wiel, Tom Heskes, Evgeni Levin
KeCo: Kernel-Based Online Co-agreement Algorithm. Discovery Science (2015)
Adriana Birlutiu, Florence d'Alché-Buc, Tom Heskes
A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions. IEEE ACM Trans. Comput. Biol. Bioinform. 12 (3) (2015)
Sanne Schoenmakers, Tom Heskes, Marcel van Gerven
Hidden Markov Models for Reading Words from the Human Brain. PRNI (2015)
Thomas Grubinger, Adriana Birlutiu, Holger Schöner, Thomas Natschläger, Tom Heskes
Domain Generalization Based on Transfer Component Analysis. IWANN (1) (2015)
Max Hinne, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven
Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates. PLoS Comput. Biol. 11 (11) (2015)
Christiaan A. de Leeuw, Joris M. Mooij, Tom Heskes, Danielle Posthuma
MAGMA: Generalized Gene-Set Analysis of GWAS Data. PLoS Comput. Biol. 11 (4) (2015)
Fabian Gieseke, Tapio Pahikkala, Tom Heskes
Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering. IDA (2015)
Binyam Gebrekidan Gebre, Peter Wittenburg, Sebastian Drude, Marijn Huijbregts, Tom Heskes
Speaker diarization using gesture and speech. INTERSPEECH (2014)
Sanne Schoenmakers, Marcel van Gerven, Tom Heskes
Gaussian mixture models improve fMRI-based image reconstruction. PRNI (2014)
Binyam Gebrekidan Gebre, Onno Crasborn, Peter Wittenburg, Sebastian Drude, Tom Heskes
Unsupervised Feature Learning for Visual Sign Language Identification. ACL (2) (2014)
Botond Cseke, Tom Heskes
Properties of Bethe Free Energies and Message Passing in Gaussian Models. CoRR (2014)
Ronald J. Janssen, Max Hinne, Tom Heskes, Marcel A. J. van Gerven
Quantifying uncertainty in brain network measures using Bayesian connectomics. Frontiers Comput. Neurosci. 8 (2014)
Mike Koeman, Tom Heskes
Mutual Information Estimation with Random Forests. ICONIP (2) (2014)
Jesse Alama, Tom Heskes, Daniel Kühlwein, Evgeni Tsivtsivadze, Josef Urban
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods. J. Autom. Reason. 52 (2) (2014)
Binyam Gebrekidan Gebre, Peter Wittenburg, Tom Heskes, Sebastian Drude
Motion history images for online speaker/signer diarization. ICASSP (2014)
Adriana Birlutiu, Tom Heskes
Using Topology Information for Protein-Protein Interaction Prediction. PRIB (2014)
Max Hinne, Luca Ambrogioni, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven
Structurally-informed Bayesian functional connectivity analysis. NeuroImage 86 (2014)
Sanne Schoenmakers, Umut Güçlü, Marcel van Gerven, Tom Heskes
Gaussian mixture models and semantic gating improve reconstructions from human brain activity. Frontiers Comput. Neurosci. 8 (2014)
Syed Abbas, Tjeerd Dijkstra, Tom Heskes
A comparative study of cell classifiers for image-based high-throughput screening. BMC Bioinform. 15 (2014)
Tom Heskes, Rob Eisinga, Rainer Breitling
A fast algorithm for determining bounds and accurate approximate p-values of the rank product statistic for replicate experiments. BMC Bioinform. 15 (2014)
Elena Sokolova, Perry Groot, Tom Claassen, Tom Heskes
Causal Discovery from Databases with Discrete and Continuous Variables. Probabilistic Graphical Models (2014)
Binyam Gebrekidan Gebre, Peter Wittenburg, Tom Heskes
Automatic sign language identification. ICIP (2013)
Binyam Gebrekidan Gebre, Peter Wittenburg, Tom Heskes
Automatic Signer Diarization - The Mover Is the Signer Approach. CVPR Workshops (2013)
Binyam Gebrekidan Gebre, Marcos Zampieri, Peter Wittenburg, Tom Heskes
Improving Native Language Identification with TF-IDF Weighting. BEA@NAACL-HLT (2013)
Joris M. Mooij, Tom Heskes
Cyclic Causal Discovery from Continuous Equilibrium Data. UAI (2013)
Sanne Schoenmakers, Markus Barth, Tom Heskes, Marcel van Gerven
Linear reconstruction of perceived images from human brain activity. NeuroImage 83 (2013)
Tom Claassen, Tom Heskes
Bayesian Probabilities for Constraint-Based Causal Discovery. IJCAI (2013)
Evgeni Tsivtsivadze, Hanneke Borgdorff, Janneke van de Wijgert, Frank H. J. Schuren, Rita Verhelst, Tom Heskes
Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data. PSL (2013)
Tom Claassen, Joris M. Mooij, Tom Heskes
Learning Sparse Causal Models is not NP-hard. UAI (2013)
Tom Claassen, Joris M. Mooij, Tom Heskes
Learning Sparse Causal Models is not NP-hard. CoRR (2013)
Wim Wiegerinck, Tom Heskes
IPF for Discrete Chain Factor Graphs CoRR (2013)
Tom Heskes, Onno Zoeter
Expectation Propogation for approximate inference in dynamic Bayesian networks CoRR (2013)
Max Hinne, Tom Heskes, Christian F. Beckmann, Marcel A. J. van Gerven
Bayesian inference of structural brain networks. NeuroImage 66 (2013)
Binyam Gebrekidan Gebre, Peter Wittenburg, Tom Heskes
The gesturer is the speaker. ICASSP (2013)
Adriana Birlutiu, Perry Groot, Tom Heskes
Efficiently learning the preferences of people. Mach. Learn. 90 (1) (2013)
Diego Vidaurre, Marcel A. J. van Gerven, Concha Bielza, Pedro Larrañaga, Tom Heskes
Bayesian Sparse Partial Least Squares. Neural Comput. 25 (12) (2013)
Evgeni Tsivtsivadze, Tom Heskes, Armand Paauw
Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains. MCS (2013)

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Publication Activity (10 Years)

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Tom Heskes