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Found 3 papers, 3 papers with code
Scalable Spike-and-Slab
Spike-and-slab priors are commonly used for Bayesian variable selection, due to their interpretability and favorable statistical properties.
Bounding Wasserstein distance with couplings
Markov chain Monte Carlo (MCMC) provides asymptotically consistent estimates of intractable posterior expectations as the number of iterations tends to infinity.
Estimating Convergence of Markov chains with L-Lag Couplings
Markov chain Monte Carlo (MCMC) methods generate samples that are asymptotically distributed from a target distribution of interest as the number of iterations goes to infinity.
Computation Methodology
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