This extended short course introduces and discusses basic concepts of machine learning and how they relate to principles and applications of control and optimization theory.
The first 4 weeks will be held given by Timm Faulwasser and team and focus on optimization aspects of the training of neural networks.
The second part is provided by Enrique Zuazua and directed towards control of dynamical systems and how this aligns with the theory of supervised learning.
The last part by Jan Heiland considers applications of neural networks for the formulation of control tasks.
|September 07: 15:00–16:40||TF/JH||01 Introduction|
|September 09: 15:00–16:40||TF||02 Questions and Challenges|
|September 14: 15:00–16:40||TF||03 Optimization VooV: 684 7858 1174|
|September 16: 15:00–16:40||TF||04 Challenges and Tasks in Optimization VooV: 714 153 178|
|September 23: 15:00–16:40||TF||05 Gaussian Processes VooV: 714 153 178|
|September 28: 15:00–16:40||TF||VooV: 684 7858 1174|
|September 30: 15:00–16:40||TF||VooV: 714 153 178|
|EZ||Note: shifted to Saturday|
|October 09: 15:00–16:40||EZ||Note: Saturday VooV: 770 795 439|
|October 12: 15:00–16:40||EZ||VooV: 684 7858 1174|
|October 14: 15:00–16:40||EZ||VooV: 714 153 178|
|October 19: 15:00–16:40||EZ||VooV: 684 7858 1174|
|October 21: 15:00–16:40||EZ||VooV: 714 153 178|
|October 26: 15:00–16:40||EZ||VooV: 684 7858 1174|
|October 28: 15:00–16:40||EZ||VooV: 714 153 178|
|November 02: 15:00–16:40||JH||17 Physics Informed Neural Network BBB|
|November 04: 15:00–16:40||JH||18 Convolutional Neural Networks Zoom: 69133989530|
|November 09: 15:00–16:40||JH||19 Wrapup and Studying in Germany Zoom: 69615001183|
|November 11: 15:00–16:40||JH||
20 Introduction to
All times are Beijing time.
All material can be found here. With file names corresponding to the lectures. Please also see the details of every lecture.
Wrapup on how Neural Networks can assist with (or even replace) the costly simulation of PDEs.
Little preview on Data encoding by NN.
What constitutes a Neural Network and how to make it physics informed.
Training an backward mode to compute the gradients for the optimization.
For all questions around studying abroad, contact the SHU international office.