Artificial Intelligence and Mathematics Research

At the 2024 Spring Central Sectional Meeting in Milwaukee, experts tackled a gap in AI literature by emphasizing rigorous mathematical foundations often overlooked. Focusing on machine learning, deep learning, and geometric analysis, the proceedings equip researchers with vital theoretical insights. This volume contains the proceedings of the 2024 Spring Central Sectional Meeting, held at the University of Wisconsin-Milwaukee, Milwaukee, WI, on April 20-21, 2024. Our motivation for this volume is to fill the void of mathematical literature in the current developments of artificial intelligence, machine learning, deep learning, geometric deep learning, geometric information theory, etc. While there are some excellent mathematical ideas in such developments, the literature is flooded by papers and books written by computer scientists and engineers that lightly touch upon these subjects, thereby missing deep mathematical understanding. This makes it difficult for anyone who wants to enter such areas of research. What is missing in the literature is exactly the theoretical mathematical background in artificial intelligence and machine learning.