Our guest speaker is Eloy Mosig from the University of Pisa.

You are all cordially invited to the CVG Seminar on October 3rd, 2025 at 2:45 pm CEST

• in person at the Institute of Computer Science: room 302, Neubrückstrasse 10, 3012 Bern
• via Zoom (passcode is 315364).

Abstract

In this talk, we study the quantitative convergence of trained shallow neural networks to their associated Gaussian processes in the infinite width limit. While previous work has established qualitative convergence under broad settings, precise, finite-width estimates remain limited, particularly during training. We provide explicit upper bounds on the quadratic Wasserstein distance between the network output and its Gaussian approximation at any positive training time, demonstrating polynomial decay with network width. Our results quantify how architectural parameters, such as width and input dimension, influence convergence, and how training dynamics affect the approximation error. This is joint work with Andrea Agazzi and Dario Trevisan.

Bio

Eloy Mosig is a PhD student at University of Pisa which is currently visiting Professor Andrea Agazzi's team at IMSV in Bern. His main research interests lie at the intersection of probability theory, machine learning and applied topology. He holds a Master's degree from University of Bologna.