EFE-based planning is formulated as variational free energy minimization with epistemic priors, decomposing into expected plan costs plus a complexity term.
Variational Inference for Dirichlet Process Mixtures
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EFE-based active inference planning is characterized as VFE on an augmented model plus entropy and planning corrections, with a derived message-passing implementation and grid-world validation.
A joint Bayesian framework with sparsity priors for simultaneous inference of NLMEM parameters and high-dimensional genetic covariate selection in population pharmacokinetics.
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Expected Free Energy-based Planning as Variational Inference
EFE-based planning is formulated as variational free energy minimization with epistemic priors, decomposing into expected plan costs plus a complexity term.
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What Type of Inference is Active Inference?
EFE-based active inference planning is characterized as VFE on an augmented model plus entropy and planning corrections, with a derived message-passing implementation and grid-world validation.
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Joint Bayesian Inference of Genetic Effect Sizes and PK Parameters in Nonlinear Mixed-Effects Models
A joint Bayesian framework with sparsity priors for simultaneous inference of NLMEM parameters and high-dimensional genetic covariate selection in population pharmacokinetics.
- Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures