Andrea Agazzi
University of Bern
Imperial College London, South Kensington Campus
–
2026 / General information
The workshop will take place at 170 Queen’s Gate, an elegant Victorian venue in South Kensington.
Running for two and a half days, the programme begins on the morning of 23 November and continues through 25 November. A dedicated poster session is scheduled for the afternoon of 24 November.
If an email window does not open, use the copy icon and paste the address into your usual email app.
2026 / Confirmed
Meet the researchers joining us in London this November. More speakers will be added as invitations are accepted.
University of Bern
TU Munich
University of Turin
Imperial College London
University of Birmingham
ENSAE Paris / CREST
Université Gustave Eiffel
University of Potsdam
Freie Universität Berlin
University of Ulm
University of Amsterdam
Inria Paris / CERMICS
New York University
University of Warwick
Inria / Université Grenoble Alpes
2026 / Registration
Registration and poster abstract submissions for the 2026 workshop are now closed.
Registration closed
We are no longer accepting registrations for the 2026 workshop. We look forward to welcoming registered participants to London.
No further registrations can be accepted.
Poster abstract submissions closed
As workshop registration is now closed, we are no longer accepting new poster abstracts.
Submission status Closed
Submission contents Title + short abstract
File format PDF · maximum 1 page
Printed posters: portrait orientation is recommended. The poster boards are 1 metre wide; please ensure your poster fits within this width.
Poster awards. We’re excited to recognise outstanding work presented in the poster session.
Already accepted? The format and board dimensions above remain applicable to accepted poster presenters.
Past events / 01—02
Two editions have already brought together the community around continuous dynamics, probabilistic inference and machine learning.
A one-day exploration of gradient-flow approaches for sampling, inference and learning—from Langevin and Wasserstein dynamics to diffusion models, robustness and sequential Bayesian methods.
Speakers
The inaugural one-day workshop connected continuous dynamics with Bayesian posterior sampling, variational inference, generative modelling and deep-learning optimisation.
Speakers