This paper provides a concise description of the free energy principle, starting from a
formulation of random dynamical systems in terms of a Langevin equation and ending with a …

This paper describes a path integral formulation of the free energy principle. The ensuing
account expresses the paths or trajectories that a particle takes as it evolves over time. The …

The aim of this paper is to introduce a field of study that has emerged over the last decade,
called Bayesian mechanics. Bayesian mechanics is a probabilistic mechanics, comprising …

The 'free energy principle'(FEP) has been suggested to provide a unified theory of the brain,
integrating data and theory relating to action, perception, and learning. The theory and …

Collective motion is ubiquitous in nature; groups of animals, such as fish, birds, and
ungulates appear to move as a whole, exhibiting a rich behavioral repertoire that ranges …

A considerable number of recent experimental and computational studies suggest that
subtle impairments of excitatory to inhibitory balance or regulation are involved in many …

For unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) networks, we propose
a unified three-dimensional (3D) spatial framework in this paper to model a general case …

This paper concerns structure learning or discovery of discrete generative models. It focuses
on Bayesian model selection and the assimilation of training data or content, with a special …

The Kalman filter is an algorithm for the estimation of hidden variables in dynamical systems
under linear Gauss-Markov assumptions with widespread applications across different …

The integration of Cognitive Radio (CR) with Unmanned Aerial Vehicles (UAVs) is an
effective step towards relieving the spectrum scarcity and empowering the UAV with a high …