Bringing together researchers at the intersection of geometric deep learning, applied geometry, and neuroscience to uncover geometric principles for neural representations

In recent years, there has been a growing appreciation for the importance of modeling the geometric structure in data — a perspective that has developed in both the geometric deep learning and applied geometry communities. In parallel, an emerging set of findings in neuroscience suggests that group-equivariance and the preservation of geometry and topology may be fundamental principles of neural coding in biology.


This workshop will bring together researchers from geometric deep learning and geometric statistics with theoretical and empirical neuroscientists whose work reveals the elegant implementation of geometric structure in biological neural circuitry. Group theory and geometry were instrumental in unifying models of fundamental forces and elementary particles in 20th-century physics. Likewise, they have the potential to unify our understanding of how neural systems form useful representations of the world.


The goal of this workshop is to unify the emerging paradigm shifts towards structured representations in deep networks and the geometric modeling of neural data — while promoting a solid mathematical foundation in algebra, geometry, and topology.




Invited Speakers and Panelists

Bruno Olshausen

UC Berkeley

Irina Higgins

DeepMind

Taco Cohen

Qualcomm

Erik Bekkers

UvA

Rose Yu

UC San Diego


Kristopher Jensen

Cambridge


Gabriel Kreiman

Harvard

Manu Madhav

UBC


Contributed Talks

John Vastola

Vanderbilt

Noah Shutty

Google

Sharvaree Vadgama

UvA

Sékou-Oumar Kaba

Mila


Sarah McGuire

Michigan State

Hamza Keurti

ETH Zurich

Federico Barbero

Oxford

Andreaa Deac

Mila

Chaitanya Joshi

Cambridge

Matthew Farrell

Harvard


Organizers

Sophia Sanborn

UC Santa Barbara

Christian Shewmake

UC Berkeley

Simone Azeglio

Institut Pasteur

Arianna Di Bernardo

Ecole Normale Superieure


Nina Miolane

UC Santa Barbara


Program Committee

Nicolas Guigui (CNRS)

Frank Nielsen (Sony CSL)

Yubei Chen (Meta AI Research)

Claire Donnat (University of Chicago)

Alessandro Sarti (CNRS)

Santiago Cadena (Max Planck School for Intelligent Systems)

Adele Myers (UC Santa Barbara)

James Whittington (Oxford / Stanford)

Tamar Flash (Weizmann Institute of Science)

Maurice Weiler (University of Amsterdam)

Elodie Maignant (Inria)

Francisco Acosta (UC Santa Barbara)

David Klindt (Meta Reality Labs)

Sarah Marzen (Claremont College)

Christopher Hillar (Awecom, Inc)

Bruno Olshausen (UC Berkeley)

Mathilde Papillon (UC Santa Barbara)

Khanh Dao Duc (UBC)

Anna Calissano (Inria)

Will Dorrell (UCL)

Alexandra Libby (Princeton)

Alice Le Brigant (Université Paris)

Erik Bekkers (University of Amsterdam)

Tatyana Sharpee (Salk Institute for Biological Studies)

Xiangru Huang (MIT)

Oded Stein (MIT)

Federico Claudi (Sainsbury Wellcome Center)

Henry Adams (Colorado State)

Emanuele Rodolà (Sapienza University)

Justin Solomon (MIT)

Stéphane Deny (Aalto University)

Dorina Thanou (EPFL)

Simon Mathis (University of Cambridge)

Dylan Paiton (ElementFi)

Pim de Haan (UvA)

Joey Bose (MILA)

Adrian Valente (Ecole Normale Superieure)

Mikail Khona (MIT)

Alex Williams (NYU / Flatiron)

Manu Madhav (UBC)

Bastian Rieck (Helmholtz Munich)

Geoffrey Woollard (UBC)

Shayan Shekarforoush (University of Toronto)

Shubhendu Trivedi

Søren Hauberg (DTU)

Blake Bordelon (Harvard)

Patrick Rubin-Delanchy (University of Bristol)

Frédéric Barbaresco (Thales)

Francesco Di Giovanni (Twitter)

Sylvain Chevallier (Univ. Paris-Saclay)

Edouard Oyallon (CNRS)

Uri Cohen (Hebrew University of Jerusalem)

Rongjie Lai (RPI)

Kathryn Hess (EPFL)

Christoph Ortner (UBC)

Boyan Beronov (UBC)

Yann Thanwerdas (Inria)

Emanuele Rossi (Twitter)

Wolfgang Polonik (UC Davis)

Noah Shutty (Google)

Davide Boscaini (Fondazione Bruno Kessler)

Kaitlin Maile (University of Toulouse)

Jacob Zavatone-Veth (Harvard)

Manos Theodosis (Harvard)

Balasubramaniam Srinivasan (Purdue)

Hannah Lawrence (MIT)

Ondrej Biza (Northeastern)

Wei Ye (University of Minnesota)

Christopher Kim (NIH)

David Klee (Northeastern)

Xiaoling Hu (Stony Brook)

Rucha Joshi (NISER)

Vincent Benenati (UC Santa Barbara)

Xinling Yu (UC Santa Barbara)

Emanuele Marconato (University of Trento)

Bilal Alsallakh (Meta)

Maksim Zhdanov (Helmholtz AI)

Donlapark Ponnoprat (Chiang Mai University)

Rana Shahroz (Vanderbilt)

Kartik Sharma (Georgia Tech)

Mitchell Ostrow (MIT)

Valentino Maiorca (Sapienza University)

Marco Fumero (Sapienza University)

David Robin (Inria)

Alison Poupin (DTU)

Hrittik Roy (DTU)

Sharvaree Vadgama (UvA)

Jonathan Huml (Harvard)

Clementine Domine (UCL)

Johan Mathe (Atmo)

Grégoire Sergeant-Perthuis (University of Artois)

Sina Tootoonian (Francis Crick Institute)

Marco Pegoraro (Sapienza University)

Chris Kymn (UC Berkeley)

Kristopher Jensen (University of Cambridge)

Ilyes Batatia (ENS Paris Saclay / University of Cambridge)

Andrew Ligeralde (UC Berkeley)