Category Theory ∩ Deep Learning: the past, the present, and the future
Event details
| Date | 19.03.2025 |
| Hour | 14:15 › 15:15 |
| Speaker | Bruno Gavranović |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Despite its remarkable success, deep learning is a young field. Like the early stages of many scientific disciplines, it is permeated by ad-hoc design decisions. From the intricacies of the implementation of backpropagation, through new and poorly understood phenomena such as double descent, scaling laws or in-context learning, to a growing zoo of neural network architectures — there are few unifying principles in deep learning, and no uniform and compositional mathematical foundation. In this talk, I will give you a sense of what the necessary components of such a foundation are, the role that category theory plays in it, and the kind of models and new capabilities this systematic approach unlocks.
Practical information
- Informed public
- Free
Organizer
- Markus Kirolos Youssef
Contact
- Maroussia Schaffner