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Piecewise Deterministic Markov Processes (PDMP)

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Meeting ID: 921 4184 5761

Passcode: 193935

Notes of the Meetings:

Slides from the talks can be found here.

Term 1:

12/10/2021: Giorgos Vasdekis (Warwick)

19/10/2021: Augustin Chevallier (Lancaster)

26/10/2021: Alice Corbella (Warwick)

02/11/2021: Sam Power (Bristol)

09/11/2021: Andi Wang (Bristol)

16/11/2021: Filippo Pagani (Cambridge)

23/11/2021: Andrea Bertazzi (Delft)

07/12/2021: Sebastiano Grazzi (Delft)


For a good literature review on PDMPs for MCMC see Joris Bierkens' webpage.

Markov Models and Optimisation, Davis (Book) (The main book concerning PDMPs)

Piecewise-Deterministic Markov Processes: A General Class of Non-Diffusion Stochastic Models, Davis (The first paper, introducing PDMPs)

Analysis Of a Nonreversible Markov Chain Sampler, Diaconis, Holmes, Neal (The idea of lifting to generate non-reversible markov chains, briefly touched upon on Meeting 1)

Piecewise Deterministic Markov Processes and their invariant measures, Durmus, Guillin, Monmarch´e (Very technical paper on ways to check when the PDMP has the right distribution. Maybe leave it for later on and proceed with caution!)

The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data, Bierkens, Fearnhead, Roberts (The main paper on the Zig-Zag process as an MCMC algorithm)

A piecewise deterministic scaling limit of Lifted Metropolis-Hastings in the Curie-Weiss model, Bierkens, Roberts (A first encounter of the Zig-Zag process)

The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method, Bouchard-Cote, Vollmer, Doucet (The main paper on the Bouncy Particle Sampler (BPS) as an MCMC algorithm)