Tom Heskes
Tom Heskes
Professor of Computer Science and Artificial Intelligence, Radboud University Nijmegen
Verified email at science.ru.nl - Homepage
Title
Cited by
Cited by
Year
MAGMA: generalized gene-set analysis of GWAS data
CA de Leeuw, JM Mooij, T Heskes, D Posthuma
PLoS Comput Biol 11 (4), e1004219, 2015
7832015
Task clustering and gating for bayesian multitask learning
B Bakker, T Heskes
Journal of Machine Learning Research 4 (May), 83-99, 2003
5792003
Practical confidence and prediction intervals
T Heskes
Advances in neural information processing systems, 176-182, 1997
3311997
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
1922003
Self-organizing maps, vector quantization, and mixture modeling
T Heskes
IEEE transactions on neural networks 12 (6), 1299-1305, 2001
1852001
On the uniqueness of loopy belief propagation fixed points
T Heskes
Neural Computation 16 (11), 2379-2413, 2004
1782004
Learning processes in neural networks
TM Heskes, B Kappen
Physical Review A 44 (4), 2718, 1991
1711991
Expectation Propogation for approximate inference in dynamic Bayesian networks
T Heskes, O Zoeter
arXiv preprint arXiv:1301.0572, 2012
1572012
Clustering ensembles of neural network models
B Bakker, T Heskes
Neural networks 16 (2), 261-269, 2003
1552003
The statistical properties of gene-set analysis
CA De Leeuw, BM Neale, T Heskes, D Posthuma
Nature Reviews Genetics 17 (6), 353, 2016
1462016
Approximate inference and constrained optimization
T Heskes, K Albers, H Kappen
arXiv preprint arXiv:1212.2480, 2012
1262012
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
1142017
On-line learning processes in artificial neural networks
TM Heskes, B Kappen
North-Holland Mathematical Library 51, 199-233, 1993
1131993
Empirical Bayes for learning to learn
TM Heskes
San Francisco: Morgan Kaufmann, 2000
1122000
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
1042014
Convexity arguments for efficient minimization of the Bethe and Kikuchi free energies
T Heskes
Journal of Artificial Intelligence Research 26, 153-190, 2006
1042006
Fractional belief propagation
W Wiegerinck, T Heskes
Advances in Neural Information Processing Systems 15, 438-445, 2003
992003
Linear reconstruction of perceived images from human brain activity
S Schoenmakers, M Barth, T Heskes, M Van Gerven
NeuroImage 83, 951-961, 2013
972013
Selecting weighting factors in logarithmic opinion pools
T Heskes
Advances in neural information processing systems, 266-272, 1998
951998
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