In this masterclass, Asier Gutiérrez, a researcher in the Life Sciences department at BSC-CNS, will walk the audience through the latest advances in Algebraic Topology applied to Neural Networks.
As it is intended for a general audience, it will not go into complex mathematical foundations, technical terms or references to articles which may be hard to understand. Instead, it will focus on describing developments in the areas concerned and the framework of possibilities in them from a practical standpoint which is accessible to listeners.
Addressed to:
- Professionals working in Artificial Intelligence (more specifically in Deep Learning) who are looking to learn about tools which they can use in their everyday activities
- Artificial Intelligence researchers who would like to further their understanding of how Deep Learning networks learn
- The general public, journalists and scientific popularisers interested in key developments in Deep Learning
