16 citations · 29 across the 4 of their papers we have counts for
4 papers
Multilevel Monte Carlo for Scalable Bayesian Computations
Mike Giles, Tigran Nagapetyan, Lukasz Szpruch +2
Markov chain Monte Carlo (MCMC) algorithms are ubiquitous in Bayesian computations. However, they need to access the full data set in order to evaluate the posterior density at eve…
Relativistic Monte Carlo
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever +2
Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Ha…
Unbiased Monte Carlo: posterior estimation for intractable/infinite-dimensional models
Sergios Agapiou, Gareth O. Roberts, Sebastian J. Vollmer
We provide a general methodology for unbiased estimation for intractable stochastic models. We consider situations where the target distribution can be written as an appropriate li…
Consistency and fluctuations for stochastic gradient Langevin dynamics
Yee Whye Teh, Alexandre Thiéry, Sebastian Vollmer
Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally expensive. Both the calculation of the acceptance probability and the creation of…