Wouter M. Kouw
TitleCited byYear
Feature-level domain adaptation
WM Kouw, LJP van der Maaten, JH Krijthe, M Loog
Journal of Machine Learning Research 17 (171), 1-32, 2016
Learning an MR acquisition-invariant representation using Siamese neural networks
WM Kouw, M Loog, LW Bartels, AM Mendrik
International Symposium on Biomedical Imaging 2019 (16), 364 - 367, 2019
CT image segmentation of bone for medical additive manufacturing using a CNN
J Minnema, M van Eijnatten, WM Kouw, F Diblen, AM Mendrik, J Wolff
Computers in Biology and Medicine 103, 130-139, 2018
On regularization parameter estimation under covariate shift
WM Kouw, M Loog
International Conference on Pattern Recognition 2016 (23), 426-431, 2017
Target contrastive pessimistic risk for robust domain adaptation
WM Kouw, M Loog
arXiv:1706.08082, 2017
A review of domain adaptation without target labels
WM Kouw, M Loog
arXiv:1901.05335, 2019
Robust importance-weighted cross-validation under sample selection bias
WM Kouw, JH Krijthe, M Loog
International Workshop on Machine Learning for Signal Processing 2019 (29), 2019
An introduction to domain adaptation and transfer learning
WM Kouw, M Loog
TU Delft Technical Report, 2018
Target contrastive pessimistic discriminant analysis
WM Kouw, M Loog
arXiv:1809.09463, 2018
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
WM Kouw, SN ōrting, J Petersen, KS Pedersen, M de Bruijne
International Conference on Information Processing in Medical Imaging 2019†…, 2019
Agent alignment through active inference
M Koudahl, WM Kouw, B De Vries
Symposium on Information Theory in the Benelux 2019 (40), 2019
Online variational message passing in autoregressive models
A Podusenko, WM Kouw, B De Vries
Symposium on Information Theory in the Benelux 2019 (40), 2019
Effects of sampling skewness of the importance-weighted risk estimator on model selection
WM Kouw, M Loog
International Conference on Pattern Recognition 2018 (24), 1468 - 1473, 2018
The event-detection gap: manual vs. automatic event detection in historical research
S Hogervorst, H Brugman, L Buitinck, M van Erp, E Klijn, WM Kouw, ...
Digital Humanities Benelux 2018, 2018
On domain-adaptive machine learning
WM Kouw
PhD Thesis, Delft University of Technology, 2018
libTLDA: A library of transfer learners and domain-adaptive classifiers
WM Kouw
Software package, doi.org/10.5281/zenodo.1214315 (github.com/wmkouw/libTLDA/), 2018
Variance reduction techniques for importance-weighted cross-validation
WM Kouw, M Loog
Dutch Conference on ICT-research 2017, 2017
Feature absence regularization for domain-adaptive learning
WM Kouw, LJP Van der Maaten
SNN Symposium - Intelligent Machines 2015, 2015
A new information-theoretic measure for saliency prediction.
WM Kouw, L Theis, H Gerhard, M Bethge
OsnabrŁck Computational Cognition Alliance Meeting 2013, 2013
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Articles 1–19