Date: morning, 19th October 2024
Embark on a comprehensive exploration of the symbiotic relationship between neural networks and differential equations. This tutorial is designed to equip participants with foundational knowledge essential for comprehending the intricate interplay between these two fields. Beginning with a friendly introduction to the theory of differential equations, we seamlessly transition to a detailed examination of the motivation, mechanisms, and hands-on application of two groundbreaking architectures: Physics-Informed Neural Networks and Neural Ordinary Differential Equations. This tutorial aims at a diverse audience, ranging from first-year PhD students to seasoned and expert researchers interested in delving into this buzzing field.
Join us for an immersive experience that goes beyond theoretical discourse. By the end of the tutorial, participants will not only grasp the fundamentals of architectures combining neural networks and differential equations but will also be empowered to apply this knowledge effectively in real-world scenarios.
Target Audience: from first-year PhD students to experienced researchers.