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Browsing by Author "Heskes, T."
Now showing items 1-50 of 261
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The stablespec package for causal discovery on cross-sectional and longitudinal data in R Rahmadi, R.; Groot, P. ; Heskes, Tom2018, 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)
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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) -
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)
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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)
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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)
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Learning the causal structure of Copula Models with Latent Variables Cui, R.; Groot, Perry ; Schauer, M.; Heskes, T.2018, Part of book or chapter of book (Globerson, A. (ed.), Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference (2018) August 6-10, 2018, Monterey, California, USA, pp. 188-197)
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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)
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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)
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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)
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Robust Estimation of Gaussian Copula Causal Structure from Mixed Data with Missing Values Cui, R.; Groot, P.C. ; Heskes, T.2017, Part of book or chapter of book (Raghavan, V. (ed.), ICDM 2017: 17th IEEE International Conference on Data Mining, 18-21 November 2017 New Orleans, Louisiana, pp. 835-840)
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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.; Möller, A.; Tucker, B.E. et al.2017, Article / Letter to editor (Monthly Notices of the Royal Astronomical Society, vol. 472, iss. 3, (2017), pp. 3101-3114)
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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)
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Package ‘stablespec’ Rahmadi, R.; Groot, P. ; Heskes, T. ; Stich, C.; Heins, M.; Knoop, H.2017, Dataset
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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. ; Platel, B. et al.2017, Article / Letter to editor (Neuroimage. Clinical, vol. 14, (2017), pp. 391-399)
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Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers 2017, Article / Letter to editor (BMC Bioinformatics, vol. 18, (2017), article 68)
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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. ; Hong, F.; Breitling, R.2017, Article / Letter to editor (Bioinformatics, vol. 33, iss. 17, (2017), pp. 2774-2775)
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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)
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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)
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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)
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Expectation Propagation 2016, Part of book or chapter of book (Sammut, C.; Webb, G.I. (ed.), Encyclopedia of Machine Learning and Data Mining, pp. 482-487)
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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)
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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)
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Copula PC Algorithm for Causal Discovery from Mixed Data Cui, R.; Groot, P. ; Heskes, T.2016, Part of book or chapter of book (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)
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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)
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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)
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The Artificial Mind’s Eye - Resisting Adversarials for Convolutional Neural Networks using Internal Projection Berntsen, H.; Kuijper, W.; Heskes, T.2016, Part of book or chapter of book (Hammer, B. (ed.), New Challenges in Neural Computation NC2 – 2016 : Workshop New Challenges in Neural Computation 2016, pp. 72-84)
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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, Part of book or chapter of book (Tourassi, G.D. (ed.), Medical Imaging 2016: Computer-Aided Diagnosis : San Diego, California, United States | February 27, 2016, pp. 97851C-97851C-7)
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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, Part of book or chapter of book (Kybic, J. (ed.), ISBI 2016 : IEEE International Symposium on Biomedical Imaging, April 13 – 16, 2016. Prague, Czech Republic, pp. 1414-1417)
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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)
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Statistical Evidence Suggests that Inattention Drives Hyperactivity/Impulsivity in Attention Deficit-Hyperactivity Disorder Sokolova, E.S. ; Groot, P. ; Claassen, T.; Hulzen, K.J.E. van ; Glennon, J.C.; Franke, B. ; Heskes, T. ; Buitelaar, J.K.2016, Article / Letter to editor (PLoS One, vol. 11, iss. 10, (2016), article e0165120)
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Computing Lower and Upper Bounds on the Probability of Causal Statements Sokolova, E.S.; Hoogman, M. ; Groot, P. ; Claassen, T.; Heskes, T.2016, Part of book or chapter of book (Antonucci, A. (ed.), PGM 2016 : Proceedings of the Eighth International Conference on Probabilistic Graphical Models, Lugano, 6-9 September 2016, pp. 487-498)
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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)
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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)
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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)
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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)
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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)
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Probabilistic clustering of the human connectome identifies communities and hubs Hinne, M. ; Ekman, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van2015, Article / Letter to editor (PLoS One, vol. 10, iss. 1, (2015), article e0117179)
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Bayesian estimation of conditional independence graphs improves functional connectivity estimates Hinne, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van2015, Article / Letter to editor (Plos Computational Biology, vol. 11, iss. 11, (2015), article e1004534)
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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)
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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)
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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. ; Kapusta, K.A. ; Klerks, E.; Knoop, H. ; Maas, D; Okkersen, C.P.; Poelmans, G.J.V. ; Rahmadi, R.; Nimwegen, M. van ; et al. et al.2015, Article / Letter to editor (Trials, vol. 16, iss. 1, (2015), pp. 1-19, article 224)
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Bayesian estimation of conditional independence graphs improves functional connectivity estimates Hinne, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van2015, Article / Letter to editor (Plos Computational Biology, vol. 11, iss. 11, (2015), article e1004534)
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Probabilistic clustering of the human connectome identifies communities and hubs Hinne, M. ; Ekman, M. ; Janssen, R.J.; Heskes, T. ; Gerven, M.A.J. van2015, Article / Letter to editor (PLoS One, vol. 10, iss. 1, (2015), article e0117179)
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Hidden Markov models for reading words from the human brain 2015, Article in monograph or in proceedings (Guerrero, J.E. (ed.), PRNI 2015 : 2015 International Workshop on Pattern Recognition in NeuroImaging, 10-12 June 2015 Stanford, CA, USA. Proceedings, pp. 89-92)
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Gaussian mixture models and semantic gating improve reconstructions from human brain activity 2015, Article / Letter to editor (Frontiers in Computational Neuroscience, vol. 8, (2015), article 173)
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Causal Discovery from Medical Data: Dealing with Missing Values and a Mixture of Discrete and Continuous Data Sokolova, E.S.; Groot, P. ; Claassen, T.; Rhein, D.T. von ; Buitelaar, J.K. ; Heskes, T.2015, Part of book or chapter of book (Holmes, J.H.; Bellazzi, R.; Sacchi, L. (ed.), Artificial Intelligence in Medicine : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings, pp. 177-181)
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Causal discovery in an adult ADHD data set suggests indirect link between DAT1 genetic variants and striatal brain activation during reward processing Sokolova, E.S.; Hoogman, M. ; Groot, P. ; Claassen, T.; Vasquez, A.A.; Buitelaar, J.K. ; Franke, B. ; Heskes, T.2015, Article / Letter to editor (American Journal of Medical Genetics. Part B : Neuropsychiatric Genetics, vol. 168, iss. 6, (2015), pp. 508-515)
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Stable Specification Searches in Structural Equation Modeling Using a Multi-objective Evolutionary Algorithm Rahmadi, R.; Groot, P. ; Heskes, T.2014, Article / Letter to editor (Seminar Nasional Aplikasi Teknologi Informasi, vol. 2014, (2014), pp. H-15 - H-20)
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