57 citations · 235 across the 17 of their papers we have counts for
18 papers
Compositionality in algorithms for smoothing
Moritz Schauer, Frank van der Meulen, Andi Q. Wang
Backward Filtering Forward Guiding (BFFG) is a bidirectional algorithm proposed in Mider et al. [2021] and studied more in depth in a general setting in Van der Meulen and Schauer…
Conditioning continuous-time Markov processes by guiding
Marc Corstanje, Frank van der Meulen, Moritz Schauer
A continuous-time Markov process can be conditioned to be in a given state at a fixed time using Doob's -transform. This transform requires the typically intractable…
Sticky PDMP samplers for sparse and local inference problems
Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen +1
We construct a new class of efficient Monte Carlo methods based on continuous-time piecewise deterministic Markov processes (PDMPs) suitable for inference in high dimensional spars…
Automatic Backward Filtering Forward Guiding for Markov processes and graphical models
Frank van der Meulen, Moritz Schauer
We incorporate discrete and continuous time Markov processes as building blocks into probabilistic graphical models with latent and observed variables. We introduce the automatic B…
Diffusion bridges for stochastic Hamiltonian systems and shape evolutions
Alexis Arnaudon, Frank van der Meulen, Moritz Schauer +1
Stochastically evolving geometric systems are studied in shape analysis and computational anatomy for modelling random evolutions of human organ shapes. The notion of geodesic path…
A piecewise deterministic Monte Carlo method for diffusion bridges
Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen +1
We introduce the use of the Zig-Zag sampler to the problem of sampling conditional diffusion processes (diffusion bridges). The Zig-Zag sampler is a rejection-free sampling scheme…