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Wouter M. Kouw
标题
引用次数
引用次数
年份
A review of domain adaptation without target labels
WM Kouw, M Loog
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
5562019
An introduction to domain adaptation and transfer learning
WM Kouw, M Loog
TU Delft Technical Report, 2018
3922018
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
1272018
Feature-level domain adaptation
WM Kouw, LJP van der Maaten, JH Krijthe, M Loog
Journal of Machine Learning Research 17 (171), 1-32, 2016
762016
The data representativeness criterion
E Schat, R van de Schoot, WM Kouw, D Veen, AM Mendrik
PLOS One 2020, 2020
27*2020
Learning an MR acquisition-invariant representation using Siamese neural networks
WM Kouw, M Loog, LW Bartels, AM Mendrik
IEEE International Symposium on Biomedical Imaging 2019 (16), 364 - 367, 2019
21*2019
Back to the future – temporal adaptation of text representations
J Bjerva, WM Kouw, I Augenstein
AAAI Conference on Artificial Intelligence 34 (5), 7440-7447, 2020
14*2020
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
WM Kouw, SN Ørting, J Petersen, KS Pedersen, M de Bruijne
International Conference on Information Processing in Medical Imaging 2019 …, 2019
122019
Robust importance-weighted cross-validation under sample selection bias
WM Kouw, JH Krijthe, M Loog
IEEE International Workshop on Machine Learning for Signal Processing 2019 (29), 2019
9*2019
On epistemics in expected free energy for linear Gaussian state space models
MT Koudahl, WM Kouw, B de Vries
Entropy 23 (12), 1565, 2021
82021
Message passing-based inference for time-varying autoregressive models
A Podusenko, WM Kouw, B de Vries
Entropy 23 (6), 683, 2021
72021
Online variational message passing in hierarchical autoregressive models
A Podusenko, WM Kouw, B de Vries
IEEE International Symposium on Information Theory 2020, 2020
62020
Technical report: an introduction to domain adaptation and transfer learning
WM Kouw, M Loog
Cornell University: Ithaca, NY, USA, 1-41, 2019
62019
On regularization parameter estimation under covariate shift
WM Kouw, M Loog
International Conference on Pattern Recognition 2016 (23), 426-431, 2017
62017
Robust domain-adaptive discriminant analysis
WM Kouw, M Loog
Pattern Recognition Letters, 1-8, 2021
5*2021
Target robust discriminant analysis
WM Kouw, M Loog
IAPR International Workshop on Statistical Pattern Recognition, 1-10, 2021
4*2021
Bayesian joint state and parameter tracking in autoregressive models
I Senoz, A Podusenko, WM Kouw, B de Vries
Conference on Learning for Dynamics and Control 2020, 2020
42020
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
42018
Variational message passing for online polynomial NARMAX identification
W Kouw, A Podusenko, M Koudahl, M Schoukens
American Control Conference, 2022
32022
Message passing-based system identification for NARMAX models
A Podusenko, S Akbayrak, I Șenöz, M Schoukens, WM Kouw
Conference on Decision and Control, 2022
22022
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