| An introduction to domain adaptation and transfer learning WM Kouw, M Loog TU Delft Technical Report, 2018 | 138 | 2018 |
| A review of domain adaptation without target labels WM Kouw, M Loog IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 135* | 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 | 66 | 2018 |
| Feature-level domain adaptation WM Kouw, LJP van der Maaten, JH Krijthe, M Loog Journal of Machine Learning Research 17 (171), 1-32, 2016 | 50 | 2016 |
| 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 | 12* | 2019 |
| The data representativeness criterion E Schat, R van de Schoot, WM Kouw, D Veen, AM Mendrik PLOS One 2020, 2020 | 7* | 2020 |
| 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 | 4* | 2020 |
| Online variational message passing in hierarchical autoregressive models A Podusenko, WM Kouw, B de Vries IEEE International Symposium on Information Theory 2020, 2020 | 4 | 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 | 4 | 2019 |
| On regularization parameter estimation under covariate shift WM Kouw, M Loog International Conference on Pattern Recognition 2016 (23), 426-431, 2017 | 4 | 2017 |
| Robust domain-adaptive discriminant analysis WM Kouw, M Loog Pattern Recognition Letters, 1-8, 2021 | 3* | 2021 |
| Target robust discriminant analysis WM Kouw, M Loog IAPR International Workshop on Statistical Pattern Recognition, 1-10, 2021 | 3* | 2021 |
| 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 | 3 | 2018 |
| 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 | 2 | 2020 |
| 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 | 2* | 2019 |
| 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 | 2 | 2018 |
| Message passing-based inference for time-varying autoregressive models A Podusenko, WM Kouw, B de Vries Entropy 23 (6), 683, 2021 | | 2021 |
| Online system identification in a Duffing oscillator by free energy minimisation WM Kouw International Workshop on Active Inference 2020 (1), 2020 | | 2020 |
| Agent alignment through active inference M Koudahl, WM Kouw, B de Vries Symposium on Information Theory in the Benelux 2019 (40), 2019 | | 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 | | 2019 |
Marco LoogDelft University of Technology & University of CopenhagenVerified email at tudelft.nl
