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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 functional. Active Inference (AIF) is a corollary of the FEP that specifica
Externí odkaz:
http://arxiv.org/abs/2306.08014
Publikováno v:
Entropy. 2023; 25(8):1138
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, which still requires error-prone and time-consuming manual derivations, is
Externí odkaz:
http://arxiv.org/abs/2306.05965
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 (AIF) is a corollary of the FEP that describes how agents explore and
Externí odkaz:
http://arxiv.org/abs/2306.02733
Autor:
Blenkinsop, Alexandra, Sofocleous, Lysandros, Di Lauro, Francesco, Kostaki, Evangelia Georgia, van Sighem, Ard, Bezemer, Daniela, van de Laar, Thijs, Reiss, Peter, de Bree, Godelieve, Pantazis, Nikos, Ratmann, Oliver
In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account for the time
Externí odkaz:
http://arxiv.org/abs/2304.06353
Autor:
Blenkinsop, Alexandra, Monod, Mélodie, van Sighem, Ard, Pantazis, Nikos, Bezemer, Daniela, de Coul, Eline Op, van de Laar, Thijs, Fraser, Christophe, Prins, Maria, Reiss, Peter, de Bree, Godelieve, Ratmann, Oliver
Amsterdam and other UNAIDS Fast-Track cities aim for zero new HIV infections. Utilising molecular and clinical data of the ATHENA observational HIV cohort, our primary aims are to estimate the proportion of undiagnosed HIV infections and the proporti
Externí odkaz:
http://arxiv.org/abs/2203.07753
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 generative model of their environment. The inference of a policy (fu
Externí odkaz:
http://arxiv.org/abs/2109.00541
Active Inference (ActInf) is an emerging theory that explains perception and action in biological agents, in terms of minimizing a free energy bound on Bayesian surprise. Goal-directed behavior is elicited by introducing prior beliefs on the underlyi
Externí odkaz:
http://arxiv.org/abs/2102.08792
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Based on a generative model (GM) and beliefs over hidden states, the free energy principle (FEP) enables an agent to sense and act by minimizing a free energy bound on Bayesian surprise. Inclusion of prior beliefs in the GM about desired states leads
Externí odkaz:
http://arxiv.org/abs/1910.09823
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 probabilistic programming frameworks has much increased over the past fe
Externí odkaz:
http://arxiv.org/abs/1811.03407