46 citations · 76 across the 6 of their papers we have counts for
6 papers
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…
Realising Synthetic Active Inference Agents, Part I: Epistemic Objectives and Graphical Specification Language
Magnus Koudahl, Thijs van de Laar, Bert de Vries
The Free Energy Principle (FEP) is a theoretical framework for describing how (intelligent) systems self-organise into coherent, stable structures by minimising a free energy funct…
Realising Synthetic Active Inference Agents, Part II: Variational Message Updates
Thijs van de Laar, Magnus Koudahl, Bert de Vries
The Free Energy Principle (FEP) describes (biological) agents as minimising a variational Free Energy (FE) with respect to a generative model of their environment. Active Inference…
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…
A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithms
Marco Cox, Thijs van de Laar, Bert de Vries
The benefits of automating design cycles for Bayesian inference-based algorithms are becoming increasingly recognized by the machine learning community. As a result, interest in pr…
A Probabilistic Modeling Approach to Hearing Loss Compensation
Thijs van de Laar, Bert de Vries
Hearing Aid (HA) algorithms need to be tuned ("fitted") to match the impairment of each specific patient. The lack of a fundamental HA fitting theory is a strong contributing facto…