Simulation-based inference with Swyft
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Europe/Amsterdam
B0.203 (University of Amsterdam)
B0.203
University of Amsterdam
Science Park 904
1098XH Amsterdam
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Description
Objective
The goal of this in-person workshop is to make progress in tackling the most difficult* parameter inference problems using state-of-the-art simulation-based inference techniques as implemented in Swyft**.
*Difficult = slow simulator/model; dozens, thousands or millions of parameters; complex posterior; unknown optimal summary statistics; ...
**Swyft is a pytorch-lightning-based implementation of truncated marginal neural ratio estimation (TMNRE), which is now successfully used for a diverse set of inference problems.
Swyft in action
Further information
The workshop is planned to be in-person. If you are interested to join online, please let us know. Depending on demand, we might change part of the workshop to a hybrid version.
Participants
Alejandra Aguirre-Santaella
Alessandro Morandini
Alex Cole
Alexandra Wernersson
Androniki Dimitriou
Benjamin Miller
Camila Correa
Christoph Weniger
Christopher Eckner
Cristina Fernández Suárez
Ebo Peerbooms
Fabian Zimmer
Florian List
Gianfranco Bertone
Guadalupe Cañas-Herrera
Guillermo Franco Abellán
James Alvey
Joanna Berteaud
Karel Geraedts
Kilian Scheutwinkel
Konstantinos Leontaridis
Kosio Karchev
Martín De los Rios
Maryam Tajalli
Mathis Gerdes
Matteo Martinelli
Noemi Anau Montel
Oleg Savchenko
Oliver Böhler
Oscar Macias
Roberto Caiozzo
Roberto Ruiz de Austri
Samuel Lange
Sebastian Hoof
Sheridan Lloyd
Shin'ichiro Ando
Sibilla Bouché
Spyridon Markesinis
Stéphane Ilic
Theophanes Karydas
Thomas Edwards
Uddipta Bhardwaj
Will Handley
Youyou Li
