Gezhi Science Hall C305, Department of Applied Mathematics,National University of Tainan
Speaker(s):
Jenn-Nan Wang (National Taiwan University)
Yueh-Cheng Kuo (National Chengchi University)
Chern-Shuh Wang (National Cheng Kung University)
Organizer(s):
Yin-Liang Huang (National University of Tainan)
Chern-Shuh Wang (National Cheng Kung University)
1. Introduction & Purposes
Inverse problems are across a wide range of real-world applications, for instance, medical imaging, geophysics, materials science, and aerodynamic, etc. However, most real-world inverse problems are ill-posed which usually causes from various uncertainties. Because of the challenges, in this course, we provide an introduction to fundamental knowledge in solving inverse problems using artificial intelligence (AI). In practice, a typical inverse problem, Kalman filtering arising from target/signal tracking, is demonstrated theoretically with numerical experiment as well. Finally, in view of realization of scientific computing in AI era, we provide a brief summary of some basic skills in the randomized numerical linear algebra.
2. Outline & Descriptions
Here is the outline of the course.
Day One (August 28)
10:00~10:50 An Introduction to AI and Inverse Problems (by J.-N. Wang)
11:00~11:50 AI and Inverse Partial Differential Equation (I) (by J.-N. Wang)
12:00~14:00 Lunch Break
14:00~14:50 AI and Inverse Partial Differential Equation (II) (by J.-N. Wang)
14:50~15:10 Tea Break
15:10~16:00 An Introduction to Randomized Numerical Linear Algebra (I) (by C.-S. Wang) 16:10~17:00 An Introduction to Randomized Numerical Linear Algebra (II) (by C.-S. Wang) 18:00 Banquet
Day Two (August 29)
10:00~10:50 An Introduction to Nonlinear Kalman Filter (by Y.-C. Kuo)
11:00~11:50 Kalman Filter for Target/Signal Tracking (I) (by Y.-C. Kuo)
12:00~14:00 Lunch Break
14:00~14:50 Kalman Filter for Target/Signal Tracking (II) (by Y.-C. Kuo)
3. Registration
https://forms.gle/JZtPXyKJSC1KKgnS9
Contact:
Murphy Yu (murphyyu@ncts.tw)
