Browsing by Author "Heskes, T.M."

Role of conduct problems in the relation between Attention-Deficit Hyperactivity disorder, substance use, and gaming

Schoenmacker, G.H.; Groenman, A.P. ; Sokolova, E.S. ; Oosterlaan, J.; Rommelse, N.N.J. ; Roeyers, H. ; Franke, B. ; Heskes, T. ; Arias Vasquez, A. ; Claassen, T.; et al.

sine al.

2020, Article / Letter to editor (European Neuropsychopharmacology, vol. 30, (2020), pp. 102-113)

Learning causal structure from mixed data with missing values using Gaussian copula models

Cui, R.; Groot, P. ; Heskes, T.

2019, Article / Letter to editor (Statistics and Computing, vol. 29, iss. 2, (2019), pp. 311-333)

Bigger Buffer k-d Trees on Multi-Many-Core Systems

Gieseke, F.; Oancea, C.E.; Mahabal, A.; Igel, C.; Heskes, T.

2019, Article in monograph or in proceedings (Senger, H. (ed.), High Performance Computing for Computational Science – VECPAR 2018: 13th International Conference, São Pedro, Brazil, September 17-19, 2018, Revised Selected Papers, pp. 202-214)

Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies

Piray, Pay.; Dezfouli, Amir; Heskes, T. ; Frank, Michael J.; Daw, Nathaniel D.

2019, Article / Letter to editor (Plos Computational Biology, vol. 15, iss. 6, (2019), pp. 1-34, article e1007043)

Gene expression dependency and interaction of functional annotation in GWAS

Leeuw, Chr. de; Posthuma, D.; Heskes, T.

2019, Article / Letter to editor (European Neuropsychopharmacology, vol. 29, (2019), pp. 1123-1124)

Large-scale local causal inference of gene regulatory relationships

Bucur, I.G.; Claassen, T.; Heskes, T.

2019, Article / Letter to editor (International Journal of Approximate Reasoning, vol. 115, iss. December, (2019), pp. 50-68)

Measuring Parkinson's disease over time: The real-world within-subject reliability of the MDS-UPDRS

Evers, L.J.W.; Krijthe, Jesse H.; Meinders, M.J. ; Bloem, B.R. ; Heskes, T.M.

2019, Article / Letter to editor (Movement Disorders, vol. 34, (2019), pp. 1480-1487)

Constraining the parameters of high-dimensional models with active learning

Caron, S.; Heskes, T. ; Otten, S.M.M.; Stienen, B.P.J.

2019, Article / Letter to editor (European Physical Journal C, vol. 79, iss. 11, (2019), pp. 1-11, article 944)

Stable specification search in structural equation models with latent variables

Rahmadi, R.; Groot, P. ; Heskes, T.

2019, Article / Letter to editor (ACM Transactions on Intelligent Systems and Technology, vol. 10, iss. 5, (2019), pp. 1-23)

A novel Bayesian approach for latent variable modeling from mixed data with missing values

Cui, R.; Bucur, I.G.; Groot, P. ; Heskes, T.

2019, Article / Letter to editor (Statistics and Computing, vol. 29, iss. 5, (2019), pp. 977-993)

Additive Dose Response Models: Defining Synergy

Lederer, S.I.; Dijkstra, T.M.H. ; Heskes, T.M.

2019, Article / Letter to editor (Frontiers in Pharmacology, vol. 10, iss. 1384, (2019), pp. 1-15)

Frontostriatal functional connectivity correlates with repetitive behaviour across autism spectrum disorder and obsessive-compulsive disorder

Akkermans, S.E.A. ; Rheinheimer, N. ; Bruchhage, Muriel M.K.; Durston, Sarah; Brandeis, Daniel; Banaschewski, Tobias; Buitelaar, J.K. ; Rooij, D. van ; Oldehinkel, Marianne ; Ruiter, S.W. de ; et al.

sine al.

2019, Article / Letter to editor (Psychological Medicine, vol. 49, iss. 13, (2019), pp. 2247-2255)

NOVEL QUANTITATIVE METHOD FOR GENETIC ASSOCIATION TESTING

Schoenmacker, G.H.; Claassen, T.; Heskes, T. ; Franke, B. ; Buitelaar, J.K. ; Arias Vasquez, A.

2019, Article / Letter to editor (European Neuropsychopharmacology, vol. 29, (2019), pp. S963-S964)

The stablespec package for causal discovery on cross-sectional and longitudinal data in R

Rahmadi, R.; Groot, P. ; Heskes, Tom

2018, Article / Letter to editor (Neurocomputing, vol. 275, iss. Supplement C, (2018), pp. 2440-2443)

Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates

Thijssen, B.; Dijkstra, T.M.H.; Heskes, T. ; Wessels, L.F.A.

2018, Article / Letter to editor (Bioinformatics, vol. 34, iss. 5, (2018), pp. 803-811)

Additive Dose Response Models: Explicit Formulation and the Loewe Additivity Consistency Condition

Lederer, S.I.; Dijkstra, T.M.H. ; Heskes, T.

2018, Article / Letter to editor (Frontiers in Pharmacology, vol. 9, (2018), pp. 1-11, article 31)

A scalable preference model for autonomous decision-making

Peters, M; Saar-Tsechansky, Maytal; Ketter, W.; Williamson, S.; Groot, P. ; Heskes, T.

2018, Article / Letter to editor (Machine Learning, vol. 107, iss. 6, (2018), pp. 1039-1068)

Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure

Leeuw, C.A. de; Stringer, S.; Dekkers, Ilona A.; Heskes, T. ; Posthuma, D.

2018, Article / Letter to editor (Nature Communications, vol. 9, (2018), article 3768)

Learning the causal structure of Copula Models with Latent Variables

Cui, R.; Groot, Perry ; Schauer, M.; Heskes, T.

2018, Article in monograph or in proceedings (Globerson, A. (ed.), Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference (2018) August 6-10, 2018, Monterey, California, USA, pp. 188-197)

Causality on longitudinal data: Stable specification search in constrained structural equation modeling

Rahmadi, R.; Groot, P. ; Rijn, M.H.C. van; Brand, J. van den; Heins, M.; Knoop, H. ; Heskes, T.

2018, Article / Letter to editor (Statistical Methods in Medical Research, vol. 27, iss. 12, (2018), pp. 3814-3834)

A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks

Bucur, I.G.; Bussel, T.; Claassen, T.; Heskes, T.

2018, Article in monograph or in proceedings (Kratochvíl, V.; Studený, M. (ed.), International Conference on Probabilistic Graphical Models, 11-14 September 2018, Prague, Czech Republic, pp. 37-48)

Handwritten characters in fMRI ('BRAINS' data set)

Schoenmakers, S. ; Barth, M. ; Heskes, T.M. ; Gerven, M.A.J. van

2018, Dataset

Handwritten digits in fMRI ('69' data set)

Gerven, M.A.J. van ; Lange, F.P. de ; Heskes, T.M.

2018, Dataset

Multi-Domain Transfer Component Analysis for Domain Generalization

Grubinger, T.; Birlutiu, Adriana ; Schöner, H.; Natschläger, T.; Heskes, T.

2017, Article / Letter to editor (Neural Processing Letters, vol. 46, iss. 3, (2017), pp. 845-855)

Causality on cross-sectional data: Stable specification search in constrained structural equation modeling

Rahmadi, R.; Groot, P. ; Heins, M.; Knoop, H.; Heskes, T.

2017, Article / Letter to editor (Applied Soft Computing, vol. 52, (2017), pp. 687-698)

Convolutional neural networks for transient candidate vetting in large-scale surveys

Gieseke, F.; Bloemen, S.; Bogaard, C. van den; Heskes, T. ; Kindler, J.; Scalzo, R.A.; Ribeiro, V.A.R.M.; Roestel, J. van; Groot, P.J. ; Yuan, F.; et al.

sine al.

2017, Article / Letter to editor (Monthly Notices of the Royal Astronomical Society, vol. 472, iss. 3, (2017), pp. 3101-3114)

Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin

Ghafoorian, M.; Karssemeijer, N. ; Heskes, T. ; Bergkamp, M.I.; Wissink, J.; Obels, J.; Keizer, K.; Leeuw, F.E. de ; Ginneken, B. van ; Marchiori, E. ; et al.

sine al.

2017, Article / Letter to editor (Neuroimage. Clinical, vol. 14, (2017), pp. 391-399)

THE STATISTICAL PROPERTIES OF GENE-SET ANALYSIS FOR GWAS DATA

Leeuw, C. de; Neale, B.; Heskes, T. ; Posthuma, D.

2017, Article / Letter to editor (European Neuropsychopharmacology, vol. 27, (2017), pp. S351)

A Causal and Mediation Analysis of the Comorbidity Between Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD)

Sokolova, E.S. ; Sluiter-Oerlemans, A.M. ; Rommelse, N.N.J. ; Groot, P. ; Hartman, C.A; Glennon, J.C.; Claassen, T.; Heskes, T. ; Buitelaar, J.K.

2017, Article / Letter to editor (Journal of Autism and Developmental Disorders, vol. 47, iss. 6, (2017), pp. 1595-1604)

Handling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD

Sokolova, E.S. ; Rhein, D.T. von ; Naaijen, J. ; Groot, P. ; Claassen, T.; Buitelaar, J.K. ; Heskes, T.M.

2017, Article / Letter to editor (International Journal of Data Science and Analytics, vol. 3, iss. 2, (2017), pp. 105-119)

Robust Estimation of Gaussian Copula Causal Structure from Mixed Data with Missing Values

Cui, R.; Groot, P.C. ; Heskes, T.

2017, Article in monograph or in proceedings (Raghavan, V. (ed.), ICDM 2017: 17th IEEE International Conference on Data Mining, 18-21 November 2017 New Orleans, Louisiana, pp. 835-840)

Massively-parallel best subset selection for ordinary least-squares regression

Gieseke, F.; Polsterer, K.L.; Mahabal, A.; Igel, C.; Heskes, T.

2017, Article in monograph or in proceedings (2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017; Hilton Hawaiian Village Resort Honolulu; United States; 27 November 2017 through 1 December 2017. Proceedings, pp. 1-8)

Robust causal estimation in the large-sample limit without strict faithfulness

Bucur, I.G.; Heskes, T. ; Claassen, T.

2017, Article in monograph or in proceedings (Aarti, S. (ed.), Proceedings of Machine Learning Research, pp. 1523-1531)

Package ‘stablespec’

Rahmadi, R.; Groot, P. ; Heskes, T. ; Stich, C.; Heins, M.; Knoop, H.

2017, Dataset

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

Eisinga, R.N. ; Heskes, T.M. ; Pelzer, B.J. ; Grotenhuis, H.F. te

2017, Article / Letter to editor (BMC Bioinformatics, vol. 18, (2017), article 68)

RankProd 2.0: A refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets

Carratore, F. del; Jankevics, A.; Eisinga, R.N. ; Heskes, T.M. ; Hong, F.; Breitling, R.

2017, Article / Letter to editor (Bioinformatics, vol. 33, iss. 17, (2017), pp. 2774-2775)

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Ghafoorian, M.; Karssemeijer, N. ; Heskes, T.M. ; Uden, I.W.M. van ; Sanchez, C.I.; Litjens, G.J.; Leeuw, F.E. de ; Ginneken, B. van ; Marchiori, E. ; Platel, B.

2017, Article / Letter to editor (Scientific Reports, vol. 7, (2017), article 5110)

Expectation Propagation

Heskes, T.

2016, Part of book or chapter of book (Sammut, C.; Webb, G.I. (ed.), Encyclopedia of Machine Learning and Data Mining, pp. 482-487)

Sparse Approximate Inference for Spatio-Temporal Point Process Models

Cseke, B. ; Zammit-Mangion, A.; Heskes, T. ; Sanguinetti, G.

2016, Article / Letter to editor (Journal of the American Statistical Association, vol. 111, iss. 516, (2016), pp. 1746-1763)

BCM: toolkit for Bayesian analysis of Computational Models using samplers

Thijssen, B.; Dijkstra, T.M.H. ; Heskes, T. ; Wessels, L.F.A.

2016, Article / Letter to editor (BMC Systems Biology, vol. 10, (2016), pp. 1-8, article 100)

Automated detection of white matter hyperintensities of all sizes in cerebral small vessel disease

Ghafoorian, M.; Karssemeijer, N. ; Uden, I.W.M. van ; Leeuw, F.E. de ; Heskes, T. ; Marchiori, E. ; Platel, B.

2016, Article / Letter to editor (Medical Physics, vol. 43, iss. 12, (2016), pp. 6246-6258)

Computing Lower and Upper Bounds on the Probability of Causal Statements

Sokolova, E.S. ; Hoogman, M. ; Groot, P. ; Claassen, T.; Heskes, T.

2016, Article in monograph or in proceedings (Antonucci, A. (ed.), PGM 2016 : Proceedings of the Eighth International Conference on Probabilistic Graphical Models, Lugano, 6-9 September 2016, pp. 487-498)

Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation

Ghafoorian, M.; Karssemeijer, N. ; Heskes, T. ; Uden, I.W.M. van ; Leeuw, F.E. de ; Marchiori, E. ; Ginneken, B. van ; Platel, B.

2016, Article in monograph or in proceedings (Kybic, J. (ed.), ISBI 2016 : IEEE International Symposium on Biomedical Imaging, April 13 – 16, 2016. Prague, Czech Republic, pp. 1414-1417)

Copula PC Algorithm for Causal Discovery from Mixed Data

Cui, R.; Groot, P. ; Heskes, T.

2016, Article in monograph or in proceedings (Frasconi, P.; Landwehr, N.; Manco, G. (ed.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II, pp. 377-392)

Exploring constraint: simulating self-organization and autogenesis in the autogenic automaton

Leijnen, S.; Heskes, T. ; Deacon, T.

2016, Article in monograph or in proceedings (Gershenson, C. (ed.), ALIFE : Proceedings of the Artificial Conference 2016, pp. 68-75)

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation

Vijverberg, Koen; Ghafoorian, M.; Uden, I.W.M. van ; Leeuw, F.-E. de; Platel, B.; Heskes, T.

2016, Article in monograph or in proceedings (Tourassi, G.D. (ed.), Medical Imaging 2016: Computer-Aided Diagnosis : San Diego, California, United States | February 27, 2016, pp. 97851C-97851C-7)

The Artificial Mind’s Eye - Resisting Adversarials for Convolutional Neural Networks using Internal Projection

Berntsen, H.; Kuijper, W.; Heskes, T.

2016, Article in monograph or in proceedings (Hammer, B. (ed.), New Challenges in Neural Computation NC2 – 2016 : Workshop New Challenges in Neural Computation 2016, pp. 72-84)

The statistical properties of gene-set analysis

Leeuw, C.A. de; Neale, B.M.; Heskes, T. ; Posthuma, D.

2016, Article / Letter to editor (Nature Reviews. Genetics, vol. 17, iss. 6, (2016), pp. 353-364)

Statistical Evidence Suggests that Inattention Drives Hyperactivity/Impulsivity in Attention Deficit-Hyperactivity Disorder

Sokolova, E.S. ; Groot, P.C. ; Claassen, T.; Hulzen, K.J.E. van ; Glennon, J.C.; Franke, B. ; Heskes, T.M. ; Buitelaar, J.K.

2016, Article / Letter to editor (PLoS One, vol. 11, iss. 10, (2016), article e0165120)

KeCo: Kernel-Based Online Co-agreement Algorithm

Wiel, L.; Heskes, T. ; Levin, E.

2015, Part of book or chapter of book (Japkowicz, N.; Matwin, S. (ed.), Discovery Science : 18th International Conference, DS 2015, Banff, AB, Canada, October 4–6, 2015, Proceedings, pp. 308-315)

Radboud Repository

Browsing by Author "Heskes, T.M."

Search Repository

Browse

All of Repository