5 citations · 5 across the 1 of their papers we have counts for
2 papers
stat.ME2017
The True Cost of Stochastic Gradient Langevin Dynamics
Tigran Nagapetyan, Andrew B. Duncan, Leonard Hasenclever +3
The problem of posterior inference is central to Bayesian statistics and a wealth of Markov Chain Monte Carlo (MCMC) methods have been proposed to obtain asymptotically correct sam…
stat.ML2016★ 5 cited
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…