Predictive coding: a theoretical and experimental review
Predictive coding offers a potentially unifying account of cortical function--postulating that the
core function of the brain is to minimize prediction errors with respect to a generative model …
core function of the brain is to minimize prediction errors with respect to a generative model …
Active inference in robotics and artificial agents: Survey and challenges
Active inference is a mathematical framework which originated in computational
neuroscience as a theory of how the brain implements action, perception and learning …
neuroscience as a theory of how the brain implements action, perception and learning …
An overview of the free energy principle and related research
The free energy principle and its corollary, the active inference framework, serve as
theoretical foundations in the domain of neuroscience, explaining the genesis of intelligent …
theoretical foundations in the domain of neuroscience, explaining the genesis of intelligent …
Kalman filters as the steady-state solution of gradient descent on variational free energy
M Baltieri, T Isomura - arXiv preprint arXiv:2111.10530, 2021 - arxiv.org
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 …
under linear Gauss-Markov assumptions with widespread applications across different …
Neural kalman filtering
The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a
previous state estimate, and a dynamics model to produce a principled estimate of the …
previous state estimate, and a dynamics model to produce a principled estimate of the …
Active inference through whiskers
Rodents use whisking to probe actively their environment and to locate objects in space,
hence providing a paradigmatic biological example of active sensing. Numerous studies …
hence providing a paradigmatic biological example of active sensing. Numerous studies …
Applications of the free energy principle to machine learning and neuroscience
B Millidge - arXiv preprint arXiv:2107.00140, 2021 - arxiv.org
In this PhD thesis, we explore and apply methods inspired by the free energy principle to two
important areas in machine learning and neuroscience. The free energy principle is a …
important areas in machine learning and neuroscience. The free energy principle is a …
Discovery of α-amylase and α-glucosidase dual inhibitors from NPASS database for management of Type 2 Diabetes Mellitus: A chemoinformatic approach
Postprandial hyperglycemia, typical manifestation of Type 2 Diabetes Mellitus (T2DM), is
associated with notable global morbidity and mortality. Preventing the advancement of this …
associated with notable global morbidity and mortality. Preventing the advancement of this …
Unbiased active inference for classical control
Active inference is a mathematical framework that originated in computational neuroscience.
Recently, it has been demonstrated as a promising approach for constructing goal-driven …
Recently, it has been demonstrated as a promising approach for constructing goal-driven …
[HTML][HTML] Numerical investigations of seismic-resilient techniques for legged fluid storage tanks utilising magnetorheological dampers
SEA Hosseini, S Beskhyroun - Structures, 2024 - Elsevier
Different energy-dissipating devices have been proposed in the literature to attenuate the
destructive effects of base excitations over fluid storage tanks. These structures have …
destructive effects of base excitations over fluid storage tanks. These structures have …