Biography
Wouter Kouw is a researcher in the Bayesian Intelligent Autonomous Systems lab at the Electrical Engineering department of TU Eindhoven. He has a dual background in neuroscience and computer science, and is most interested in neuro-inspired forms of artificial intelligence. His research focuses on designing, developing and analyzing probabilistic machine learning systems that learn from interactions with their environment, most notably active inference agents. Internally, these agents perform Bayesian inference by way of message passing in graphical models. They are deployed to mobile robots to assist humans with dangerous, dirty or dull work.
- Intelligent autonomous systems
- Probabilistic machine learning
- Variational Bayesian inference
- Neural information processing
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PhD in Computer Science, 2018
Delft University of Technology
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MSc in Neuroscience, 2013
Maastricht University
Publications
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.
Bayesian autoregression to optimize temporal Matérn-kernel Gaussian process hyperparameters.
International Conference on Probabilistic Numerics, 2025.
Online Bayesian system identification in multivariate autoregressive models via message passing.
IEEE European Control Conference, 2025.
Coupled autoregressive active inference agents for control of multi-joint dynamical systems.
International Workshop on Active Inference, 2024.
Message passing-based Bayesian control of a cart-pole system.
International Workshop on Active Inference, 2024.
