Vorlesungsverzeichnis
Vorlesung im Detail
Neural networks for solving PDEs (Digital)
- Digital: Mi 12:00 2h
- DPL:A:-:-
- DPL:B:-:2
- DPL:E:-:-
- MAMA:-:7:MAT-761
- TMAMA:-:7:MAT-761
- WIMAMA:-:7:MAT-761
1.Mathematical Model of Artificial Neural Network
2.Activation Function
3. Neural Network Architecture
- Feed Forward Neural networks
- Recurrent Neural networks
- cellular Neural networks
- Finite Element Neural networks
- Radial Basis Function Neural networks
4. Optimization algorithms
5.Learning in Neural Networks
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
6. Learning Algorithm
- BP Algorithm
- the RPROP learning Algorithm
- Genetic Algorithm
Neural Networks Methods for Solving Partial differential equations
1.Method of Multilayer Perceptron Neural Networks
2. Method of cellular Neural networks
3.Method of Radial Basis Function Neural networks
4.Method of Finite Element Neural networks
Die Veranstaltung ist auch für das Masterstudium Data Science wählbar.
- No text book is specified but the following reference books may be some of use and help
- 1. Deep Learning by Ian Goodfellow , Yoshua Bengio and Aaron Courville
Übung zur Veranstaltung
- n.V.