Ph.D. Course on

Scientific Machine Learning

Kongens Lyngby, June 13thth to June 17thth 2022

The listed topics will be covered in the course. The course is partly based on the lecture notes from MIT's 18.337 Parallel Computing and Scientific Machine Learn-ing. book.sciml.ai.

1. Introduction to Scientific Machine Learning (SciML)

2. Physics-Informed Neural Networks

3. Automatic Differentiation and Differentiable Pro-gramming

4. Neural Differential Equations

5. Universal Differential Equations and Symbolic Re-gression

6. Neural Operators

Matematiktovet, DTU - Bygning 303b, DK-2800 Lyngby
dcamm@mat.dtu.dk