Publications | Wouter M. Kouw

Wouter M. Kouw.
Bayesian autoregression to optimize temporal Matérn-kernel Gaussian process hyperparameters.
International Conference on Probabilistic Numerics, 2025.

Sepideh Adamiat, Wouter M. Kouw, Bert De Vries.
Spike-timing dependent plasticity for Bernoulli message passing.
International Workshop on Active Inference, 2025.

Wouter M. Kouw, Tim Nisslbeck, Wouter Nuijten.
Message passing-based inference in an autoregressive active inference agent.
International Workshop on Active Inference, 2025.

Thijs Jenneskens, Wouter M. Kouw.
Effects of dynamic goal prior specification on grid-world agent trajectories.
International Workshop on Active Inference, 2025.

Tim Nisslbeck, Wouter M. Kouw.
Factor graph-based online Bayesian identification and component evaluation for multivariate autoregressive exogenous input models.
MDPI Entropy | Special Issue on Advances in Probabilistic Machine Learning, 2025.

Tim Nisslbeck, Wouter M. Kouw.
Online Bayesian system identification in multivariate autoregressive models via message passing.
IEEE European Control Conference, 2025.

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

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

Wouter M. 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 M. Kouw.
Bayesian inference of collision avoidance intent during ship encounters.
IEEE Transactions on Automation Science and Engineering, 2024.

Wouter M. 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 M. Kouw.
Message-passing-based system identification for NARMAX models.
Conference on Decision and Control, 2022.

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

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

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

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

Wouter M. 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 M. Kouw, Duco Veen, Adriënne Mendrik.
The data representativeness criterion.
PLOS One, 2020.

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

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

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

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

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

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

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

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

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