Swiss Equivariant Learning Workshop
CO2 - EPFL
Lausanne, Switzerland
11-14 July 2022
Small Workshop about equivariant methods for machine learning applications
Update 14.06.2022:
We are happy to announce that we are able to accept all applications for attendance given that we have managed to find a larger lecture hall on EPFL campus.
The workshop will focus on equivariant machine learning for the physical sciences in Lausanne during the 11-14th of July.
This workshop will comprise:
A few, largely pedagogical, talks put together jointly by two experts try to understand the current state of the field from various perspectives, highlighting similarities and differences between methods as well as open questions
Space for a number of hands-on tutorials to demonstrate a code or tool with the idea being that participants have something tangible to take away and use after the meeting (e.g. a jupyter notebook, runnable scripts, etc)
A number of discussion sessions where we dig deeper into particular topics or ideas so as to capitalise on the presence of numerous experts, and finally,
A number of more traditional applications or methods contributed talks to understand the breadth of applicability of these new learning models and perhaps discuss challenges faced when training such models.
Registration still possible!
Confirmed speakers
Ivan Diaz (Bern Hospital)
Boris Kozinsky (Harvard University)
Ilyes Batatia (University of Cambridge)
Michele Ceriotti (EPFL)
Kristof Schuett (Technische Universität Berlin)
Francesco Cagnetta (EPFL)
Guillaume Fraux (EPFL)
Maurice Weiler (University of Amsterdam)
Taco Cohen (Qualcomm, potentially remote)
Andrea Grisafi (ENS Paris)
Moritz Thürlemann (ETH Zürich)
Venue
The workshop will take place in:
EPFL CO2 Auditorium
1015 Lausanne, Switzerland
Nearby hotels (known from the organizers):
Organizers
Simon Batzner
Harvard
Albert Musaelian
Harvard
Mario Geiger
MIT
Tess Smidt
MIT
Jigyasa Nigam
EPFL
Martin Uhrin
EPFL
Josh Rackers
Sandia National Labs
Thomas Hardin
Sandia National Labs