We are excited to announce the next Munich AI Lecture featuring Prof. Guido Montúfar, Professor of Mathematics and of Statistics & Data Science at the University of California, Los Angeles, and leader of the Mathematical Machine Learning research group at the Max Planck Institute for Mathematics in the Sciences, MPI MiS. He serves as a core Principal Investigator in the SECAI Zuse School of Excellence in AI (Leipzig–Dresden).
Event Details:
🎤 Title: Deep Learning Theory: What we know, what we are learning, and what remains unclear
📅 Date and Time: July 17, 2025 at 5 pm CET
📍 Location: Room B006, Main LMU Building, Geschwister-Scholl-Platz 01, 80539 Munich
Abstract
Deep learning has revolutionized artificial intelligence and a wide range of applied domains, driving transformative progress in computer vision, language processing, and scientific discovery. This talk surveys the vibrant and rapidly evolving landscape of deep learning theory—an effort to uncover the mathematical foundations of learning with neural networks. We will review key theoretical insights into optimization dynamics, implicit biases of learning algorithms, and the generalization behavior of deep models—highlighting connections to classical learning theory, high dimensional statistics, and approximation theory. Along the way, we will discuss some of the major successes in analyzing overparameterized regimes, as well as open challenges in understanding feature learning and generalization under moderate overparameterization. The talk will also spotlight emerging phenomena such as benign overfitting, grokking, and delayed generalization, illustrating the depth and complexity of ongoing research questions that challenge traditional notions.
More information is available at the website of Munich AI Lectures
