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Implementation of a coupled Metropolis-Hasting Algorithm in Jax. Project done as part of the Bayesian Machine Learning course by Rémi Bardenet and Julyan Arbel.

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unbiased_mcmc_with_couplings

Implementation of "Unbiased Markov-Chain Monte Carlo estimators with couplings". Project done as part of the Bayesian Machine Learning course by Rémi Bardenet and Julyan Arbel.

It includes a coupled Metropolis-Hasting algorithm, the maximal coupling and its generalization, the modified Thorisson's Algorithm.

The R companion-code of the paper is available at https://github.com/pierrejacob/unbiasedmcmc.

How?

This package requires jax and numpy. You can use pip install -e . to install the package. See the experiments folder for some examples of how to use the package.

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Implementation of a coupled Metropolis-Hasting Algorithm in Jax. Project done as part of the Bayesian Machine Learning course by Rémi Bardenet and Julyan Arbel.

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