4 citations · 7 across the 20 of their papers we have counts for
6 papers · 1 filter
Spike-Timing-Dependent Plasticity for Bernoulli Message Passing
Sepideh Adamiat, Wouter M. Kouw, Bert de Vries
Bayesian inference provides a principled framework for understanding brain function, while neural activity in the brain is inherently spike-based. This paper bridges these two pers…
A Spiking Neural Network Implementation of Gaussian Belief Propagation
Sepideh Adamiat, Wouter M. Kouw, Bert de Vries
Bayesian inference offers a principled account of information processing in natural agents. However, it remains an open question how neural mechanisms perform their abstract operat…
Message passing-based inference in an autoregressive active inference agent
Wouter M. Kouw, Tim N. Nisslbeck, Wouter L. N. Nuijten
We present the design of an autoregressive active inference agent in the form of message passing on a factor graph. Expected free energy is derived and distributed across a plannin…
Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
Wouter M. Kouw
Gaussian processes are important models in the field of probabilistic numerics. We present a procedure for optimizing Matérn kernel temporal Gaussian processes with respect to the…
Online Bayesian system identification in multivariate autoregressive models via message passing
T. N. Nisslbeck, Wouter M. Kouw
We propose a recursive Bayesian estimation procedure for multivariate autoregressive models with exogenous inputs based on message passing in a factor graph. Unlike recursive least…
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…