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
10152015
Task clustering and gating for bayesian multitask learning
BJ Bakker, TM Heskes
6242003
Practical confidence and prediction intervals for prediction tasks
TM Heskes, W Wiegerinck, HJ Kappen
PROGRESS IN NEURAL PROCESSING, 128-135, 1997
3641997
Energy functions for self-organizing maps
T Heskes
Kohonen maps, 303-315, 1999
2101999
Stable fixed points of loopy belief propagation are minima of the Bethe free energy
T Heskes
Advances in neural information processing systems 15, 359-366, 2003
2022003
Self-organizing maps, vector quantization, and mixture modeling
T Heskes
IEEE transactions on neural networks 12 (6), 1299-1305, 2001
1872001
On the uniqueness of loopy belief propagation fixed points
T Heskes
Neural Computation 16 (11), 2379-2413, 2004
1852004
Learning processes in neural networks
TM Heskes, B Kappen
Physical Review A 44 (4), 2718, 1991
1741991
The statistical properties of gene-set analysis
CA De Leeuw, BM Neale, T Heskes, D Posthuma
Nature Reviews Genetics 17 (6), 353, 2016
1722016
Expectation Propagation for approximate inference in dynamic Bayesian networks
T Heskes, O Zoeter
arXiv preprint arXiv:1301.0572, 2012
1642012
Clustering ensembles of neural network models
B Bakker, T Heskes
Neural networks 16 (2), 261-269, 2003
1592003
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
1472017
Approximate inference and constrained optimization
T Heskes, K Albers, H Kappen
arXiv preprint arXiv:1212.2480, 2012
1282012
On-line learning processes in artificial neural networks
TM Heskes, B Kappen
North-Holland Mathematical Library 51, 199-233, 1993
1161993
Empirical Bayes for learning to learn
TM Heskes
San Francisco: Morgan Kaufmann, 2000
1152000
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
1132014
Convexity arguments for efficient minimization of the Bethe and Kikuchi free energies
T Heskes
Journal of Artificial Intelligence Research 26, 153-190, 2006
1112006
Fractional belief propagation
W Wiegerinck, T Heskes
Advances in Neural Information Processing Systems 15, 438-445, 2003
1062003
Linear reconstruction of perceived images from human brain activity
S Schoenmakers, M Barth, T Heskes, M Van Gerven
NeuroImage 83, 951-961, 2013
1002013
Selecting weighting factors in logarithmic opinion pools
T Heskes
Advances in neural information processing systems, 266-272, 1998
991998
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