139 citations · 616 across the 32 of their papers we have counts for
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Adaptive schemes for piecewise deterministic Monte Carlo algorithms
Andrea Bertazzi, Joris Bierkens
The Bouncy Particle sampler (BPS) and the Zig-Zag sampler (ZZS) are continuous time, non-reversible Monte Carlo methods based on piecewise deterministic Markov processes. Experimen…
The Boomerang Sampler
Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani +1
This paper introduces the Boomerang Sampler as a novel class of continuous-time non-reversible Markov chain Monte Carlo algorithms. The methodology begins by representing the targe…
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…