6th Sequential Monte Carlo Workshop (SMC 2024)
The SMC 2024 conference brought together researchers and practitioners in Sequential Monte Carlo (SMC) methods to discuss cutting-edge advancements in computational statistics and Bayesian inference. Participants engaged in lectures, discussions, and workshops on topics like particle filtering, importance sampling, and the applications of SMC across scientific fields. The event fostered collaboration and knowledge exchange on how these techniques can address complex, high-dimensional problems, emphasizing practical applications and theoretical innovations in the field.
Dates: May 13–17, 2024
Location: International Centre for Mathematical Sciences (ICMS), Edinburgh, Scotland
Organizers: Víctor Elvira (University of Edinburgh), Dan Crisan (Imperial College London), Jana de Wiljes (University of Potsdam), and Joaquín Míguez (Universidad Carlos III de Madrid)
Official website: https://www.icms.org.uk/SMC2024
Videos: Below are recorded sessions from the SMC 2024 workshop. Click on the thumbnails to watch each video on YouTube.
Christian Robert (Université Paris Dauphine PSL & University of Warwick) - Sampling advances by adaptive regenerative processes and importance Monte Carlo
Joaquín Míguez (Universidad Carlos III de Madrid) - A Sequential Discretisation Scheme for Stochastic Differential Equations
Axel Finke (Loughborough University) - Particle-MALA and Particle-mGRAD: Gradient-based MCMC methods
Francesca Crucinio (King's College London) - A connection between Tempering and Entropic Mirror Descent
Fredrik Lindsten (Linköping University) - Sequential Monte Carlo guidance of (discrete) diffusion models
Christophe Andrieu (University of Bristol) - Monte Carlo sampling with integrator snippets
Anthony Lee (University of Bristol) - Mixing time of the conditional backward sampling particle filter
Arnaud Doucet (University of Oxford & Google DeepMind) - Diffusion models for sampling
Yunpeng Li (University of Surrey) - Normalising flow-based differentiable particle filters
Nicola Branchini (University of Edinburgh) - Generalizing self-normalized importance sampling with couplings
Simo Särkkä (Aalto University) - Parallel filtering and smoothing methods for state-space models
Pierre Del Moral (Inria) - A variational approach to nonlinear and interacting diffusions
Alexandros Beskos (University College London) - Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions
Daniel Paulin (University of Edinburgh) - Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients
Adam Johansen (University of Warwick) - Divide and Conquer Sequential Monte Carlo with Inexact Gradients
Sara Pérez Vieites (Aalto University) - Learning the number of particles in nested filtering
Marcelo Gomes da Silva Bruno (ITA, Brazil) - Sequential Monte Carlo Methods for Distributed Bayesian Filtering on Manifolds
Nicolas Chopin (ENSAE Paris, IPP) - Unbiased estimation of smooth functions