392173 Vertiefung Neuronale Netze (V) (WiSe 2019/2020)
Contents, comment
-
- Topological Maps: Self-Organizing Maps, Growing Neural Gas, Hyperbolic SOM, Local Linear Maps
- Mixture Models: Gaussian Mixture Models, Gaussian Mixture Regression, Gaussian Processes
- Recurrent Neural Nets: Dynamics, Stability, applications: Hopfield net, CLM, ...
- Graph Networks: Processing Structural Information
- Generative Models: Generative Adversarial Networks (GAN), Actor-Critic, Variational Autoencoders
- Deep Reinforcement Learning
The lecture will be given in English language if desired by the audience.
Slides will be in English in any case.
Requirements for participation, required level
-
recommendd prerequisites:
- Machine Learning basics
- Neural Networks basics
External comments page
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-VNN Vertiefung Neuronale Netze | Vertiefung Neuronale Netze | Ungraded examination
Graded examination |
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
No more requirements
No eLearning offering available
- Registered number: 23
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- Address:
- WS2019_392173@ekvv.uni-bielefeld.de
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- Coverage:
- 8 Students to be reached directly via email
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- Last update basic details/teaching staff:
- Tuesday, June 18, 2019
- Last update times:
- Monday, October 14, 2019
- Last update rooms:
- Monday, October 14, 2019
- Type(s) / SWS (hours per week per semester)
- lecture (V) / 2
- Department
- Faculty of Technology
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