4 citations · 7 across the 20 of their papers we have counts for
8 papers · 1 filter
Spike-based Belief Propagation in Nonlinear Dynamical Systems
Sepideh Adamiat, Hongye Wang, Wouter M. Kouw +1
This paper presents a Bayesian control framework that integrates spike-based dynamics with probabilistic inference for adaptive control. Bayesian inference is widely regarded as a…
A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression
Wouter W. L. Nuijten, Esther G. van Pelt, Albert Podusenko +2
Multi-output Gaussian process regression scales cubically in the number of observations times outputs, and dense kernel-matrix methods need bespoke handling whenever different outp…
Expected free energy as an information constraint on the Bethe Lagrangian
Wouter M. Kouw
Active inference selects actions by minimising an expected free energy functional over predicted futures. However, adding an expectation over yet-unobserved outcomes means the free…
Expected Free Energy-based Informative Path Planning for Robotic Mars Exploration
Ajith Anil Meera, Pablo Lanillos, Wouter Kouw
An autonomous robot efficiently exploring an unknown environment, such as looking for water sources on Mars, faces two simultaneous demands: building an accurate information map wh…
Expected Free Energy-based Planning as Variational Inference
Wouter W. L. Nuijten, Thijs van de Laar, Bert de Vries
Planning under uncertainty requires agents to balance goal achievement with information gathering. Active inference addresses this through the Expected Free Energy (EFE), a cost fu…
Composing Non-Conjugate Factor Graphs with Closed-Form Variational Inference
Mykola Lukashchuk, Kyrylo Yemets, Wouter M. Kouw +4
Stacking probabilistic building blocks into deeper architectures typically breaks closed-form inference. We show that closed-form inference can be preserved. We identify five facto…
Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization
Ajith Anil Meera, Wouter Kouw
We propose an Expected Free Energy-based acquisition function for Bayesian optimization to solve the joint learning and optimization problem, i.e., optimize and learn the underlyin…
Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study
Andrew Stirling, Mykola Lukashchuk, Dmitry Bagaev +2
This letter extends the exactly sparse Gaussian variational inference (ESGVI) algorithm for state estimation in two complementary directions. First, ESGVI is generalized to operate…