A joint Bayesian framework with sparsity priors for simultaneous inference of NLMEM parameters and high-dimensional genetic covariate selection in population pharmacokinetics.
Variational Inference for Dirichlet Process Mixtures
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DP-GMM based probabilistic frontier prioritization enhances two multi-agent exploration algorithms with average gains of 10% and 14% in simulations across varied conditions and real dual-drone tests.
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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.
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Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures
DP-GMM based probabilistic frontier prioritization enhances two multi-agent exploration algorithms with average gains of 10% and 14% in simulations across varied conditions and real dual-drone tests.