Browsing by Author "Heskes, T.M."

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

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)

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)

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)

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)

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, Tom

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.

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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.

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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)

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)

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)

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)

Package ‘stablespec’

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

2017, Dataset

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)

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)

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)

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)

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)

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)

Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering

Gieseke, F.C.; Pahikkala, T.; Heskes, T.

2015, Part of book or chapter of book (Fromont, E.; Bie, T. De; Leeuwen, M. van (ed.), Advances in Intelligent Data Analysis XIV : 14th International Symposium, IDA 2015, Saint Etienne, France, October 22–24, 2015, Proceedings, pp. 95-107)

Domain Generalization Based on Transfer Component Analysis

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

2015, Part of book or chapter of book (Rojas, I.; Joya, G.; Catala, A. (ed.), Advances in Computational Intelligence, pp. 325-334)

A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions

Birlutiu, A.; d'Alche-Buc, F.; Heskes, T.

2015, Article / Letter to editor (Ieee/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, iss. 3, (2015), pp. 538-550)

MAGMA: Generalized Gene-Set Analysis of GWAS Data

Leeuw, C.A. de; Mooij, J.M. ; Heskes, T. ; Posthuma, D.

2015, Article / Letter to editor (Plos Computational Biology, vol. 11, iss. 4, (2015), article e10042)

Probabilistic clustering of the human connectome identifies communities and hubs

Hinne, M. ; Ekman, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van

2015, Article / Letter to editor (PLoS One, vol. 10, iss. 1, (2015), article e0117179)

Bayesian estimation of conditional independence graphs improves functional connectivity estimates

Hinne, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van

2015, Article / Letter to editor (Plos Computational Biology, vol. 11, iss. 11, (2015), article e1004534)

Small white matter lesion detection in cerebral small vessel disease

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

2015, Article in monograph or in proceedings (Hadjiiski, L.M. (ed.), Medical Imaging 2015: Computer-Aided Diagnosis, Orlando, Florida, United States, February 21, 2015, pp. 941411-1-941411-6)

Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling

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

2015, Article in monograph or in proceedings (Douzal-Chouakria, A. (ed.), AALTD 2015 : Advanced Analytics and Learning on Temporal Data : 1st International Workshop on Advanced Analytics and Learning on Temporal Data co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015) Porto, Portugal, September 11, 2015, pp. 101-107)

Cognitive behaviour therapy plus aerobic exercise training to increase activity in patients with myotonic dystrophy type 1 (DM1) compared to usual care (OPTIMISTIC): study protocol for randomised controlled trial

Engelen, B.G.M. van ; Groot, P.C. ; Abghari, S.; Aschrafi, A. ; Bouman, S.F.; Cornelissen, Y.; Glennon, J.C.; Heerschap, A. ; Heskamp, L.; Heskes, T. ; et al.

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2015, Article / Letter to editor (Trials, vol. 16, iss. 1, (2015), pp. 1-19, article 224)

Bayesian estimation of conditional independence graphs improves functional connectivity estimates

Hinne, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van

2015, Article / Letter to editor (Plos Computational Biology, vol. 11, iss. 11, (2015), article e1004534)

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