Ph.D. Course on Scientific Machine Learning

Description

The course is offered with support from the DTU Compute Graduate School (ITMAN) and the Danish Center for Applied Mathematics and Mechanics (DCAMM) at Technical University of Denmark.

The aim of the course is to introduce the students to some of the modern methods and algorithms used in Scientific Machine Learning (SciML), and let the students experience these methods on elementary computer experiments.

The PhD course covers several topics in SciML: neural differential equations, universal differential equations, physics-informed neural networks (PINN),automatic differentiation (AD) / differentiable programming, neural operators, symbolic regression, and more. The objective is to give the student an overview of the "tools" available and how they can be modified for particular SciML applications. The course is partly based on the lecture notes from MIT's 18.337 Parallel Computing and Scientific Machine Learning.

The course will be given by:
Dr. Christopher Rackauckas, Massachusetts Institute of Technology (MIT), Boston, United States, meREMOVEMEchrisrackauckas.com

Period	13 Jun 2022 → 17 Jun 2022
Event type	Course
Location	Kgs. Lyngby, DenmarkShow on map