Publications |

Chengfeng Jia, Jie Ma, Wouter Kouw.
Multiple variational Kalman-GRU for ship trajectory prediction with uncertainty.
IEEE Transactions on Aerospace and Electronic Systems, 2024.

Wouter Kouw.
Planning to avoid ambiguous states through Gaussian approximations to non-linear sensors in active inference agents.
International Workshop on Active Inference, 2024.

Sepideh Adamiat, Wouter Kouw, Bart van Erp, Bert de Vries.
Message passing-based Bayesian control of a Cart-Pole system.
International Workshop on Active Inference, 2024.

Tim Nisslbeck, Wouter Kouw.
Coupled autoregressive active inference agents for control of multi-joint dynamical systems.
International Workshop on Active Inference, 2024.

Wouter Kouw, Caspar Gruijthuijsen, Lennart Blanken, Enzo Evers, Timothy Rogers.
Bayesian grey-box identification of convection effects in heat transfer dynamics.
IEEE International Conference on Control Technology and Applications, 2024.

Chengfeng Jia, Jie Ma, Bert de Vries, Wouter Kouw.
Bayesian inference of collision avoidance intent during ship encounters.
IEEE Transactions on Automation Science and Engineering, 2024.

Wouter Kouw.
Information-seeking polynomial NARX model-predictive control through expected free energy minimization.
IEEE Control Systems Letters, 2023.

Albert Podusenko, Semih Akbayrak, Ismail Senoz, Maarten Schoukens, Wouter Kouw.
Message-passing-based system identification for NARMAX models.
Conference on Decision and Control, 2022.

Alp Sarı, Tak Kaneko, Lense Swaenen, Wouter Kouw.
Variational Bayes for robust radar single object tracking.
IEEE Workshop on Signal Processing Systems, 2022.

Wouter Kouw, Albert Podusenko, Magnus Koudahl, Maarten Schoukens.
Variational message passing for online polynomial NARMAX identification.
IEEE American Control Conference, 2022.

Magnus Koudahl, Wouter Kouw, Bert de Vries.
On epistemics in expected free energy for linear Gaussian state space models.
MDPI Entropy | Special Issue on Emerging Methods in Active Inference, 2021.

Albert Podusenko, Wouter Kouw, Bert de Vries.
Message passing-based inference for time-varying autoregressive models.
MDPI Entropy | Special Issue on Bayesian Inference in Probabilistic Graphical Models, 2021.

Wouter Kouw, Marco Loog.
Robust domain-adaptive discriminant analysis.
Pattern Recognition Letters, 2021.

Wouter Kouw, Marco Loog.
Target robust discriminant analysis.
IAPR International Workshop on Statistical Pattern Recognition, 2021.

Wouter Kouw.
Online system identification in a Duffing oscillator by free energy minimisation.
International Workshop on Active Inference, 2020.

Evelien Hart, Rens van de Schoot, Wouter Kouw, Duco Veen, Adriënne Mendrik.
The data representativeness criterion.
PLOS One, 2020.

Albert Podusenko, Wouter Kouw, Bert de Vries.
Online variational message passing in hierarchical autoregressive models.
IEEE International Symposium on Information Theory, 2020.

Ismail Senoz, Albert Podusenko, Wouter Kouw, Bert de Vries.
Bayesian joint state and parameter tracking in autoregressive models.
Conference on Learning for Decision and Control, 2020.

Johannes Bjerva, Wouter Kouw, Isabelle Augenstein.
Back to the future - temporal adaptation of text representations.
AAAI Conference on Artificial Intelligence, 2019.

Wouter Kouw, Marco Loog.
A review of domain adaptation without target labels.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.

Wouter Kouw, Marco Loog.
Robust importance-weighted cross-validation under sample selection bias.
IEEE International Workshop on Machine Learning for Signal Processing, 2019.

Wouter Kouw, Silas Ørting, Jens Petersen, Kim Pedersen, Marleen de Bruijne.
A cross-center smoothness prior for variational Bayesian brain tissue segmentation.
International Conference on Information Processing in Medical Imaging, 2019.

Wouter Kouw, Marco Loog, Wilbert Bartels, Adriënne Mendrik.
Learning an MR acquisition-invariant representation using Siamese neural networks.
IEEE International Symposium on Biomedical Imaging, 2019.

Jordi Minnema, Maureen van Eijnatten, Wouter Kouw, Faruk Diblen, Adriënne Mendrik, Jan Wolff.
CT image segmentation of bone for medical additive manufacturing using a CNN.
Computers in Biology & Medicine, 2018.

Wouter Kouw, Marco Loog.
Effects of sampling skewness of the importance-weighted risk estimator on model selection.
International Conference on Pattern Recognition, 2018.

Wouter Kouw, Marco Loog.
An introduction to domain adaptation and transfer learning.
Technical Report - TU Delft, 2017.

Wouter Kouw, Marco Loog.
On regularization parameter estimation under covariate shift.
International Conference on Pattern Recognition, 2016.

Wouter Kouw, Laurens van der Maaten, Jesse Krijthe, Marco Loog.
Feature-level domain adaptation.
Journal of Machine Learning Research, 2016.