Diagrammatic Intuition and Deep Learning in Mathematics

06 Oct 2023, by ablahatherell in Sponsored events

15 – 19 July 2024

York University, UK

Supported by The Heilbronn Institute Small Grants Scheme

The workshop will centre around the search for diagrammatic and categorical intuition and the use of deep learning ideas in order to develop a greater understanding of classical questions in mathematics. It will be a mixture of survey and in-depth research talks. The main goal of the workshop will be the showcasing of work of promising early career participants, both via short talks and a conference poster session.


Michael Bate (York)
Chris Bowman (York)
Brent Everitt (York)
Harry Geranios (York)
Jonathan Gruber (York)
Amit Hazi (York)


Anna Beliakova (UZH)
Maud De Visscher (London)
Olivier Dudas (Marseille)
Nicolle Gonzalez (Berkeley)
Eugene Gorsky (UC Davis)
Mickail Khovanov (Columbia)
Henry Kvinge (Pacific North West Labs)
Rob Muth (Duquesne)
Loïc Poulain d’Andecy (Reims)
Radmila Sazdanovic (North Carolina State)
Liron Speyer (OIST)
Catharina Stroppel (Bonn)
Daniel Tubbenhauer (Sydney)
Petar Veličković (Google DeepMind/Cambridge)
Adam Wagner (Worcester)
Paul Wedrich (Hamburg)

More information on the conference website