6th Workshop on Sequential Monte Carlo Methods (SMC 2024)

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6th Workshop on Sequential Monte Carlo Methods (SMC 2024)

 13 - 17 May 2024
Register to attend online

ICMS, Bayes Centre, Edinburgh

 Enquiries

Due to high demand, this event will now run in a hybrid format. Registration for online attendance will close Friday 3 May 2024, 15.00 BST.

Scientific Organisers:

  • Víctor Elvira, University of Edinburgh
  • Jana de Wiljes, University of Potsdam
  • Dan Crisan, Imperial College London

About:

Sequential Monte Carlo (SMC) methods, also known as particle filters or particle methods, have become popular and powerful tools for computational inference in complex probabilistic models used in many and varied fields and applications. The research community includes practitioners and theoreticians at the intersection of statistics, computer science, electrical engineering, and applied mathematics. The interest in SMC methods have rapidly grown in the last decade, jointly with the new challenges and the enormous potential of SMC to tackle high-impact problems in applied sciences (e.g., meteorology, biomedicine, robotics, etc.). The main objectives of the meeting are:  

1. to bring together researchers developing and using SMC methods in a diversity of scientific and engineering fields, both in academia and the industry, and

2. to open the field to researchers and users who are new to SMC methods. We will emphasize the interaction of SMC with related areas of research (such as machine learning or data science) where computational inference plays a key role.

Below, we provide a list of key theoretical and methodological topics, as well as application areas.

  Theory & Methodology

  • Particle filtering/SMC methods

  • Kalman filtering

  • Data assimilation

  • State space models

  • Numerical methods for stochastic partial differential equations (SPDEs)

  • Adaptive importance sampling

  • Sequential Markov-chain Monte Carlo (MCMC) methods

  • Stability of optimal filters

  • Multi-level Monte Carlo

  Applications

  • Multi-target tracking

  • Radar and sonar signal processing

  • Localization and tracking with sensor networks

  • Numerical weather prediction

  • Climate modeling and prediction

  • Biomedical signal processing

  • Astrophysics and cosmology

  • Smart grids and industrial applications

  • Quantitative finance

Finally, this event is linked to the Summer School on Bayesian filtering: fundamental theory and numerical methods (SSBF), which will be held also at ICMS on 6-10 May 2024 (i.e., the week before this workshop).

Participation:

SMC 2024 has reached maximum capacity for in-person attendance. All registered participants have been contacted by ICMS with full details including the link to pay the registration fee. If you have not received this email, please check your junk/spam inbox or get in touch.

Due to high demand, this event will now run in a hybrid format. Registration for online attendance will close Friday 3 May 2024, 15.00 BST. You will also receive the Zoom link by 17.00 BST on this day. You may need to check your junk/spam inbox for this email. Please note, online attendance will allow you to watch/interact during talks only. There are no hybrid facilities in the catering area.

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Programme

MONDAY 13 MAY 2024
09.00 - 09.25 Registration and Refreshments
09.25 - 09.30 Welcome and Housekeeping
09.30 - 10.15 Christian Robert, Université Paris Dauphine PSL & University of Warwick Sampling advances by adaptive regenerative processes and importance Monte Carlo
10.15 - 11.00 Sahani Pathiraja, UNSW Sydney
11.00 - 11.30 Refreshments
11.30 - 12.15 Joaquín Míguez, Universidad Carlos III de Madrid
12.15 - 13.00 Axel Finke, Loughborough University Particle­-MALA and Particle­-mGRAD: Gradient­-based MCMC methods for high­-dimensional state-space models
13.00 - 14.30 Lunch
14.30 - 15.15 Francesca Crucinio, King's College London A connection between Tempering and Entropic Mirror Descent
15.15 - 16.00 Fredrik Lindsten, Linköping University
16.00 - 16.30 Refreshments
16.30 - 17.45 Poster session 1
TUESDAY 14 MAY 2024
09.00 - 09.30 Refreshments
09.30 - 10.15 Christophe Andrieu, University of Bristol Monte Carlo sampling with integrator snippets
10.15 - 11.00 Anthony Lee, University of Bristol Mixing time of the conditional backward sampling particle filter
11.00 - 11.30 Refreshments
11.30 - 12.15 Arnaud Doucet, University of Oxford
12.15 - 13.00 Meetings & discussion
13.00 - 14.30 Lunch
14.30 - 15.20 Yunpeng Li, University of Surrey Normalising flow-based differentiable particle filters
15.20 - 16.10 Neil Chada, Heriot Watt University Multilevel Bayesian Deep Neural Networks
16.10 - 16.40 Refreshments
16.40 - 17.55 Poster session 2
19.00 - 22.00 Conference Dinner
WEDNESDAY 15 MAY 2024
09.00 - 09.30 Refreshments
09.30 - 10.15 Nick Whiteley, University of Bristol Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods
10.15 - 11.00 Jana de Wiljes, TU Ilmenau
11.00 - 11.30 Refreshments
11.30 - 12.15 Oana Lang, Imperial College London
12.15 - 13.00 Meetings & discussion
13.00 - 14.30 Lunch
14.30 - 15.20 Nicola Branchini, University of Edinburgh
15.20 - 16.10 Simo Särkkä, Aalto University Parallel filtering and smoothing methods for state-space models
16.10 - 16.40 Refreshments
16.40 - 17.55 Poster session 3
THURSDAY 16 MAY 2024
09.00 - 09.30 Refreshments
09.30 - 10.15 Pierre Del Moral, Inria
10.15 - 11.00 Alexandros Beskos, University College London Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions
11.00 - 11.30 Refreshments
11.30 - 12.15 Daniel Paulin, University of Edinburgh Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients
12.15 - 13.00 Adam Johansen, University of Warwick Divide and Conquer Sequential Monte Carlo: Some Properties and Application
13.00 - 14.30 Lunch
14.30 - 16.10 Meetings & discussion
FRIDAY 17 MAY 2024
09.00 - 09.30 Refreshments
09.30 - 10.15 Sara Pérez Vieites, Aalto University
10.15 - 11.00 Marcelo Gomes da Silva Bruno, ITA, Brazil Sequential Monte Carlo Methods for Distributed Bayesian Filtering on Manifolds
11.00 - 11.30 Refreshments
11.30 - 12.15 Jeremy Heng, ESSEC Business School Computational Doob's h-transforms for online filtering
12.15 - 13.00 Nicolas Chopin, ENSAE Paris, IPP Unbiased estimation of smooth functions
13.00 - 14.30 Lunch and end of workshop