research
∙
05/12/2023
Nonparametric Bayesian inference for stochastic processes with piecewise constant priors
We present a survey of some of our recent results on Bayesian nonparamet...
share
research
∙
03/08/2022
Introduction to Automatic Backward Filtering Forward Guiding
In this document I aim to give an informal treatment of automatic Backwa...
research
∙
11/22/2021
Conditioning continuous-time Markov processes by guiding
A continuous-time Markov process X can be conditioned to be in a given s...
research
∙
03/15/2021
Sticky PDMP samplers for sparse and local inference problems
We construct a new class of efficient Monte Carlo methods based on conti...
research
∙
10/07/2020
Automatic Backward Filtering Forward Guiding for Markov processes and graphical models
We incorporate discrete and continuous time Markov processes as building...
research
∙
02/03/2020
Diffusion bridges for stochastic Hamiltonian systems with applications to shape analysis
Stochastically evolving geometric systems are studied in geometric mecha...
research
∙
01/16/2020
A piecewise deterministic Monte Carlo method for diffusion bridges
We introduce the use of the Zig-Zag sampler to the problem of sampling o...
research
∙
11/23/2019
Bayesian nonparametric estimation in the current status continuous mark model
In this paper we consider the current status continuous mark model where...
research
∙
09/02/2019
Nonparametric Bayesian estimation of a concave distribution function with mixed interval censored data
Assume we observe a finite number of inspection times together with info...
research
∙
03/26/2019
Decompounding discrete distributions: A non-parametric Bayesian approach
Suppose that a compound Poisson process is observed discretely in time a...
research
∙
10/17/2018
Bayesian wavelet de-noising with the caravan prior
According to both domain expertise knowledge and empirical evidence, wav...
research
∙
10/03/2018
Simulation of elliptic and hypo-elliptic conditional diffusions
Suppose X is a multidimensional diffusion process. Assume that at time z...
research
∙
05/15/2018
Nonparametric Bayesian volatility learning under microstructure noise
Aiming at financial applications, we study the problem of learning the v...
research
∙
04/10/2018
Fast and scalable non-parametric Bayesian inference for Poisson point processes
We study the problem of non-parametric Bayesian estimation of the intens...
research
∙
01/30/2018
Nonparametric Bayesian volatility estimation
Given discrete time observations over a fixed time interval, we study a ...
research
∙
01/08/2018
Bayesian estimation of a decreasing density
Suppose X_1,..., X_n is a random sample from a bounded and decreasing de...
research
∙
12/11/2017
Continuous-discrete smoothing of diffusions
Suppose X is a multivariate diffusion process that is observed discretel...
research
∙
08/16/2017