12 citations · 25 across the 8 of their papers we have counts for
9 papers
Continuously-Tempered PDMP Samplers
Matthew Sutton, Robert Salomone, Augustin Chevallier +1
New sampling algorithms based on simulating continuous-time stochastic processes called piece-wise deterministic Markov processes (PDMPs) have shown considerable promise. However,…
Spectral Subsampling MCMC for Stationary Multivariate Time Series with Applications to Vector ARTFIMA Processes
Mattias Villani, Matias Quiroz, Robert Kohn +1
Spectral subsampling MCMC was recently proposed to speed up Markov chain Monte Carlo (MCMC) for long stationary univariate time series by subsampling periodogram observations in th…
The reproducing Stein kernel approach for post-hoc corrected sampling
Liam Hodgkinson, Robert Salomone, Fred Roosta
Stein importance sampling is a widely applicable technique based on kernelized Stein discrepancy, which corrects the output of approximate sampling algorithms by reweighting the em…
Spectral Subsampling MCMC for Stationary Time Series
Robert Salomone, Matias Quiroz, Robert Kohn +2
Bayesian inference using Markov Chain Monte Carlo (MCMC) on large datasets has developed rapidly in recent years. However, the underlying methods are generally limited to relativel…
Implicit Langevin Algorithms for Sampling From Log-concave Densities
Liam Hodgkinson, Robert Salomone, Fred Roosta
For sampling from a log-concave density, we study implicit integrators resulting from -method discretization of the overdamped Langevin diffusion stochastic differential equatio…
Unbiased and Consistent Nested Sampling via Sequential Monte Carlo
Robert Salomone, Leah F. South, Christopher Drovandi +2
We introduce a new class of sequential Monte Carlo methods which reformulates the essence of the nested sampling method of Skilling (2006) in terms of sequential Monte Carlo techni…
Monte Carlo Estimation of the Density of the Sum of Dependent Random Variables
Patrick J. Laub, Robert Salomone, Zdravko I. Botev
We study an unbiased estimator for the density of a sum of random variables that are simulated from a computer model. A numerical study on examples with copula dependence is conduc…
Accurate Computation of the Distribution of Sums of Dependent Log-Normals with Applications to the Black-Scholes Model
Zdravko Botev, Robert Salomone, Daniel MacKinlay
We present a new Monte Carlo methodology for the accurate estimation of the distribution of the sum of dependent log-normal random variables. The methodology delivers statistically…
Stratified Splitting for Efficient Monte Carlo Integration
Radislav Vaisman, Robert Salomone, Dirk P. Kroese
The efficient evaluation of high-dimensional integrals is of importance in both theoretical and practical fields of science, such as data science, statistical physics, and machine…