Assuming exponential-family distributions for variational posteriors and priors extends the free-energy principle–predictive coding correspondence to exhibit biological neural properties such as nonlinearity, heterogeneity, and positive firing rates, with training via local plasticity rules.
Learning probability distributions of sensory inputs with Monte Carlo predictive coding.PLOS Computational Biology, 20(10): e1012532, October 2024
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Extended predictive coding framework as variational free-energy minimisation under exponential-family assumption
Assuming exponential-family distributions for variational posteriors and priors extends the free-energy principle–predictive coding correspondence to exhibit biological neural properties such as nonlinearity, heterogeneity, and positive firing rates, with training via local plasticity rules.