Author: Denise Holt

This paper introduces a generative modelling approach to neurophenomenology, merging computational neuroscience with phenomenological philosophy. It r…

The paper introduces Action Perception Divergence (APD), a framework for categorizing objective functions in intelligent agents. It distinguishes betw…

The paper explores why Bayesian inference in the brain contributes to poor performance on explicit probabilistic reasoning tasks. It distinguishes bet…

This research explores canonical neural networks, demonstrating that they perform active inference and learning via rate coding models. It reveals tha…

The post introduces pymdp, a Python library designed for simulating active inference in complex systems using partially-observable Markov Decision Pro…

The paper discusses advancements in unsupervised reinforcement learning (RL), focusing on enhancing data efficiency in high-dimensional environments. …

The paper discusses the construction of spatial maps for navigation, proposing that a unified mechanism underlies the chunking of sensory data in both…

The Free Energy Principle (FEP) proposes that random dynamical systems minimize an upper bound on surprisal through weak coupling. This paper reformul…

The abstract discusses active inference, linked to the free energy principle, as a method for understanding certain random dynamical systems resemblin…