Automatic Backward Filtering Forward Guiding for Markov processes and graphical models

4 code implementations • 7 Oct 2020 • Frank van der Meulen, Moritz Schauer

The guided generative model can be incorporated in different approaches to efficiently sample latent states and parameters conditional on observations.

Computation Methodology Primary 62H22, 62M20, secondary 60J05, 60J25

Diffusion bridges for stochastic Hamiltonian systems and shape evolutions

1 code implementation • 3 Feb 2020 • Alexis Arnaudon, Frank van der Meulen, Moritz Schauer, Stefan Sommer

Stochastically evolving geometric systems are studied in shape analysis and computational anatomy for modelling random evolutions of human organ shapes.

Numerical Analysis Computational Engineering, Finance, and Science Numerical Analysis Computational Physics

A piecewise deterministic Monte Carlo method for diffusion bridges

3 code implementations • 16 Jan 2020 • Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen, Moritz Schauer

We introduce the use of the Zig-Zag sampler to the problem of sampling conditional diffusion processes (diffusion bridges).

Statistics Theory Probability Methodology Statistics Theory

Nonparametric Bayesian volatility learning under microstructure noise

1 code implementation • 15 May 2018 • Shota Gugushvili, Frank van der Meulen, Moritz Schauer, Peter Spreij

In this work, we study the problem of learning the volatility under market microstructure noise.

Fast and scalable non-parametric Bayesian inference for Poisson point processes

4 code implementations • 10 Apr 2018 • Shota Gugushvili, Frank van der Meulen, Moritz Schauer, Peter Spreij

The observations are assumed to be $n$ independent realisations of a Poisson point process on the interval $[0, T]$.

Methodology 62G20 (Primary) 62M30 (Secondary)

Nonparametric Bayesian volatility estimation

1 code implementation • 30 Jan 2018 • Shota Gugushvili, Frank van der Meulen, Moritz Schauer, Peter Spreij

Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation of the volatility coefficient of a stochastic differential equation.

Methodology Statistics Theory Statistical Finance Statistics Theory 62G20 (Primary), 62M05 (Secondary)

Continuous-discrete smoothing of diffusions

1 code implementation • 11 Dec 2017 • Marcin Mider, Moritz Schauer, Frank van der Meulen

At each observation time, a transformation of the state of the process is observed with noise.

Computation 60J60, 65C05 (Primary), 62F15 (Secondary)

Guided proposals for simulating multi-dimensional diffusion bridges

1 code implementation • 14 Nov 2013 • Moritz Schauer, Frank van der Meulen, Harry van Zanten

A Monte Carlo method for simulating a multi-dimensional diffusion process conditioned on hitting a fixed point at a fixed future time is developed.

Probability 60J60 (Primary), 65C30 (Secondary), 65C05