Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hird, Max"'
Autor:
Hird, Max, Maire, Florian
Autocorrelations in MCMC chains increase the variance of the estimators they produce. We propose the occlusion process to mitigate this problem. It is a process that sits upon an existing MCMC sampler, and occasionally replaces its samples with ones
Externí odkaz:
http://arxiv.org/abs/2411.11983
This paper aims at improving the convergence to equilibrium of finite ergodic Markov chains via permutations and projections. First, we prove that a specific mixture of permuted Markov chains arises naturally as a projection under the KL divergence o
Externí odkaz:
http://arxiv.org/abs/2411.08295
Autor:
Hird, Max, Livingstone, Samuel
Linear transformation of the state variable (linear preconditioning) is a common technique that often drastically improves the practical performance of a Markov chain Monte Carlo algorithm. Despite this, however, the benefits of linear preconditionin
Externí odkaz:
http://arxiv.org/abs/2312.04898
We study a recently introduced gradient-based Markov chain Monte Carlo method based on 'Barker dynamics'. We provide a full derivation of the method from first principles, placing it within a wider class of continuous-time Markov jump processes. We t
Externí odkaz:
http://arxiv.org/abs/2012.09731