Julia implementation of some ABC algorithms.
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Updated
May 16, 2018 - Julia
Julia implementation of some ABC algorithms.
BayesianNonparametrics in julia
Algorithms and case studies for the paper "Accelerating delayed-acceptance Markov chain Monte Carlo algorithms".
Julia package for Bayesian joint latent class models of longitudinal and time-to-event models
Bayesian optimization is a method of finding the maximum of expensive cost functions. Bayesian optimization employs the Bayesian technique of setting a prior over the objective function and combining it with evidence to get a posterior function. This permits a utility-based selection of the next observation to make on the objective function, wh…
Markov Chain Monte Carlo convergence diagnostics in Julia
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
A common framework for implementing and using log densities for inference.
Bayesian optimization for Julia
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Julia implementation of Ge et al's PRScs
Approximate variational inference in Julia
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