14 citations · 42 across the 7 of their papers we have counts for
7 papers
Convergence of random-weight sequential Monte Carlo methods
Paul B. Rohrbach, Robert L. Jack
We investigate the properties of a sequential Monte Carlo method where the particle weight that appears in the algorithm is estimated by a positive, unbiased estimator. We present…
Multilevel simulation of hard-sphere mixtures
Paul B. Rohrbach, Hideki Kobayashi, Robert Scheichl +2
We present a multilevel Monte Carlo simulation method for analysing multi-scale physical systems via a hierarchy of coarse-grained representations, to obtain numerically-exact resu…
Critical point for de-mixing of binary hard spheres
Hideki Kobayashi, Paul B. Rohrbach, Robert Scheichl +2
We use a two-level simulation method to analyse the critical point associated with demixing of binary hard sphere mixtures. The method exploits an accurate coarse-grained model wit…
Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19
Yuting I. Li, Günther Turk, Paul B. Rohrbach +12
Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired. We present a Baye…
Inference, prediction and optimization of non-pharmaceutical interventions using compartment models: the PyRoss library
R. Adhikari, Austen Bolitho, Fernando Caballero +15
PyRoss is an open-source Python library that offers an integrated platform for inference, prediction and optimisation of NPIs in age- and contact-structured epidemiological compart…
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format
Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck +1
Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up lar…
Correction of coarse-graining errors by a two-level method: application to the Asakura-Oosawa model
Hideki Kobayashi, Paul B. Rohrbach, Robert Scheichl +2
We present a method that exploits self-consistent simulation of coarse-grained and fine-grained models, in order to analyse properties of physical systems. The method uses the coar…