Numerical Methods for Algorithmic Systems and Neural Networks

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Kinnewig, S.; Kolditz, L.; Roth, J.; Wick; T.: Numerical Methods for Algorithmic Systems and Neural Networks. Lecture Notes. Hannover : Institut für Angewandte Mathematik, Leibniz Universität Hannover, 2022, 441 S. DOI: https://doi.org/10.15488/11897

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Sum total of downloads: 10,297




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Abstract: 
These lecture notes are devoted to numerical concepts and solution of algorithmic systems and neural networks. The course is divided into four parts: traditional AI (artificial intelligence), deep learning in neural networks, applications to (and with) differential equations, and project work. Throughout this course an emphasis is on mathematical ingredients from which several are rigorously proven. In the project work, the participants usually form groups and work together on a given problem to train themselves on mathematical modeling, design of algorithms, implementation, and analysis and intepretation of the simulation results.
License of this version: CC BY-NC-ND 3.0 DE
Document Type: Other
Publishing status: draft
Issue Date: 2022-03-21
Appears in Collections:Fakultät für Mathematik und Physik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 8,614 83.66%
2 image of flag of United States United States 293 2.85%
3 image of flag of China China 186 1.81%
4 image of flag of Israel Israel 138 1.34%
5 image of flag of Austria Austria 127 1.23%
6 image of flag of Netherlands Netherlands 88 0.85%
7 image of flag of United Kingdom United Kingdom 81 0.79%
8 image of flag of Russian Federation Russian Federation 74 0.72%
9 image of flag of France France 72 0.70%
10 image of flag of India India 35 0.34%
    other countries 589 5.72%

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