An introductory lecture series by Professor Gitta Kutyniok (LMU, Munich) on the mathematics of deep learning, accompanied by a workshop.
LMS invited lectures by Gitta Kutyniok
- Lecture 1: Introduction to Deep Neural Networks
- Lecture 2: Deep Neural Networks: From Approximation to Expressivity
- Lecture 3: Deep Neural Networks: Analyzing the Training Algorithm
- Lecture 4: Deep Neural Networks: The Mystery of Generalization
- Lecture 5: Deep Neural Networks: Opening the Black Box via Explainability Methods
- Lecture 6: Deep Neural Networks: Towards Robustness
- Lecture 7: Deep Neural Networks: Can Deep Neural Networks be Provably Fair?
- Lecture 8: Inverse Problems meet Deep Learning: Optimal Hybrid Methods
- Lecture 9: Partial Differential Equations meet Deep Learning: Beating the Curse of Dimensionality
- Lecture 10: Mathematical Foundations of Deep Learning: Potential, Limitations, and Future Directions
- Peter Bartlett (UC Berkeley)
- Weinan E (Princeton University)
- Klaus-Robert Müller (TU Berlin)
- Rebecca Willett (University of Chicago)
The annual Invited Lecturers scheme aims to bring a distinguished overseas mathematician to the United Kingdom to present a small course of about ten lectures spread over a week. Each course of Invited Lectures is on a major field of current mathematical research, and is instructional in nature, being directed both at graduate students beginning research and at established mathematicians who wish to learn about a field outside their own research specialism.