Tom Heskes
Tom Heskes
Professor of Computer Science and Artificial Intelligence, Radboud University Nijmegen
Geverifieerd e-mailadres voor science.ru.nl - Homepage
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MAGMA: generalized gene-set analysis of GWAS data
CA de Leeuw, JM Mooij, T Heskes, D Posthuma
PLoS computational biology 11 (4), 2015
6742015
Task clustering and gating for bayesian multitask learning
B Bakker, T Heskes
Journal of Machine Learning Research 4 (May), 83-99, 2003
5592003
Practical confidence and prediction intervals
T Heskes
Advances in neural information processing systems, 176-182, 1997
3161997
Energy functions for self-organizing maps
T Heskes
Kohonen maps, 303-315, 1999
2051999
Stable fixed points of loopy belief propagation are local minima of the bethe free energy
T Heskes
Advances in neural information processing systems, 359-366, 2003
1902003
Self-organizing maps, vector quantization, and mixture modeling
T Heskes
IEEE transactions on neural networks 12 (6), 1299-1305, 2001
1842001
On the uniqueness of loopy belief propagation fixed points
T Heskes
Neural Computation 16 (11), 2379-2413, 2004
1762004
Learning processes in neural networks
TM Heskes, B Kappen
Physical Review A 44 (4), 2718, 1991
1701991
Clustering ensembles of neural network models
B Bakker, T Heskes
Neural networks 16 (2), 261-269, 2003
1532003
Expectation Propogation for approximate inference in dynamic Bayesian networks
T Heskes, O Zoeter
arXiv preprint arXiv:1301.0572, 2012
1522012
The statistical properties of gene-set analysis
CA De Leeuw, BM Neale, T Heskes, D Posthuma
Nature Reviews Genetics 17 (6), 353, 2016
1392016
Approximate inference and constrained optimization
T Heskes, K Albers, H Kappen
arXiv preprint arXiv:1212.2480, 2012
1262012
Empirical Bayes for learning to learn
TM Heskes
San Francisco: Morgan Kaufmann, 2000
1092000
Location sensitive deep convolutional neural networks for segmentation of white matter hyperintensities
M Ghafoorian, N Karssemeijer, T Heskes, IWM van Uden, CI Sanchez, ...
Scientific Reports 7 (1), 1-12, 2017
1072017
On-line learning processes in artificial neural networks
TM Heskes, B Kappen
Math. foundations of neural networks, Elsevier, Amsterdam, 199-233, 1993
1061993
Convexity arguments for efficient minimization of the Bethe and Kikuchi free energies
T Heskes
Journal of Artificial Intelligence Research 26, 153-190, 2006
1042006
Premise selection for mathematics by corpus analysis and kernel methods
J Alama, T Heskes, D Kühlwein, E Tsivtsivadze, J Urban
Journal of Automated Reasoning 52 (2), 191-213, 2014
972014
Fractional belief propagation
W Wiegerinck, T Heskes
Advances in Neural Information Processing Systems 15, 438-445, 2003
972003
Linear reconstruction of perceived images from human brain activity
S Schoenmakers, M Barth, T Heskes, M Van Gerven
NeuroImage 83, 951-961, 2013
922013
Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior
MAJ Van Gerven, B Cseke, FP De Lange, T Heskes
NeuroImage 50 (1), 150-161, 2010
922010
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