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• SS23_PMI

Probabilistic Modling and Inference

General Information

Topics

This course provides a series of lectures on probabilistic modeling and inference, covering the following topics:

• Bayesian learning
• Variational inference
• Sampling methods
• Bayesian deep learning
• Generative modeling
• Gaussian process and Bayesian optimization

Enrollment / Limited number of participants

If you intend to participate, please send an e-mail to nakajima@tu-berlin.de with the title "Probabilistic Modeling and Inference Enrollment," and the main text including your name and Matr. Nr. Participation spots are assigned on a first come/first serve basis.

Students from other universities

If you are not a student at TU and want to earn credit, you have to solicit ''Nebenhörerschaft'':

• First fill the online ''form'' with the following details on the final page.

  Course title and type	Program number	Number of course hours per week (SWS)	Lecturer
  Julia Programming for Machine Learning	0434 L 543	2	Adrian Hill

• Send the form to one of the trainers (see contact information above) to sign
• Then send the signed form to Manuela Gadow (manuela.gadow at tu-berlin.de), who is authorized to sign on behalf of our dean.

• After getting your signed form back send it together with your current matriculation letter ('Immatrikulationsbescheinigung') to the student registration office (nebenhoerer@studsek.tu-berlin.de).

Please make sure to trigger the above process on time. You may need to go through some bureaucracy to attain ISIS (the university's web portal) access, which is necessary to submit the mandatory homework.