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

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

• Full name
• Matr. no.
• Affiliation (University, Department, master/bachelor)
• Email address
• Module name (CA, ML, or standalone (only for non-TU students))

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
  Probabilistic Modeling and Inference	0434 L 503	2	Shinichi Nakajima

• 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).