10 citations · 11 across the 5 of their papers we have counts for
5 papers
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…
Expected Free Energy-based Planning as Variational Inference
Bert de Vries, Wouter Nuijten, Thijs van de Laar +13
We address the problem of planning under uncertainty, where an agent must choose actions that not only achieve desired outcomes but also reduce uncertainty. Traditional methods oft…
Improved Depth Estimation of Bayesian Neural Networks
Bart van Erp, Bert de Vries
This paper proposes improvements over earlier work by Nazareth and Blei (2022) for estimating the depth of Bayesian neural networks. Here, we propose a discrete truncated normal di…
Automating Model Comparison in Factor Graphs
Bart van Erp, Wouter W. L. Nuijten, Thijs van de Laar +1
Bayesian state and parameter estimation have been automated effectively in a variety of probabilistic programming languages. The process of model comparison on the other hand, whic…
Active Inference and Epistemic Value in Graphical Models
Thijs van de Laar, Magnus Koudahl, Bart van Erp +1
The Free Energy Principle (FEP) postulates that biological agents perceive and interact with their environment in order to minimize a Variational Free Energy (VFE) with respect to…