This paper introduces a class of Monte Carlo algorithms which are based on the simulation
of a Markov process whose quasi-stationary distribution coincides with a distribution of …

This paper introduces a class of Monte Carlo algorithms which are based upon simulating a
Markov process whose quasi-stationary distribution coincides with the distribution of interest …

Diffusions are a fundamental class of models in many fields, including finance, engineering,
and biology. Simulating diffusions is challenging as their sample paths are infinite …

Real-world multistage stochastic optimization problems are often characterized by the fact
that the decision maker may take actions only at specific points in time, even if relevant data …

We introduce verifiable criteria for weak posterior consistency of Bayesian nonparametric
inference for jump diffusions with unit diffusion coefficient and uniformly Lipschitz drift and …

The paper introduces a class of Monte Carlo algorithms which are based on the simulation
of a Markov process whose quasi-stationary distribution coincides with a distribution of …

In many domains where mathematical modelling is applied, a deterministic description of the
system at hand is insufficient, and so it is useful to model systems as being in some way …