LMS Invited Lecture Series 2022: The Mathematics of Deep Learning

Isaac Newton Institute, UK and online
Start date
Meeting Date
Professor Gitta Kutyniok (LMU, Munich)


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

    Accompanying lectures

  • Peter Bartlett (UC Berkeley)
  • Weinan E (Princeton University)
  • Klaus-Robert Müller (TU Berlin)
  • Rebecca Willett (University of Chicago)

Further information and Registration

The Invited Lecture Series

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.