AATRN Networks seminar, November 7 at 5pm CET by Cristian Bodnar
AATRN Networks
Dear AATRN Networks members,
Our first online seminar will be Tuesday, November 7, at 5pm CET / 11am Eastern Daylight Time.
Speaker: Cristian Bodnar
Title: A Sheaf-based Approach to Graph Neural Networks
Abstract: The multitude of applications where data is attached to spaces with non-Euclidean structure has driven the rise of the field of Geometric Deep Learning (GDL). Nonetheless, from many points of view, geometry does not always provide the right level of abstraction to study all the spaces that commonly emerge in such settings. For instance, graphs, by far the most prevalent type of space in GDL, do not even have a geometrical structure in the strict sense. In this talk, I will explore how we can take a sheaf-theoretic perspective of the field with a focus on understanding and developing new Graph Neural Network models.
We will meet in the following coordinates.
https://rtucloud1.zoom.us/j/92064430961?pwd=TkY1VU52MHlyN29ON2IvblFNVXVoZz09
Meeting ID: 920 6443 0961
Passcode: 862736
We will meet the first Tuesday of every month and you can follow our future planned list of speakers in our website https://sites.google.com/view/aatrn-networks-seminar
You may also be interested in adding AATRN’s Google calendar, which contains other seminar information.
Best,
The AATRN Networks organizers
Daniela Egas Santander, Jānis Lazovskis, Henri Riihimäki, Jason Smith
https://sites.google.com/view/aatrn-networks-seminar