Differences between revisions 8 and 10 (spanning 2 versions)
Revision 8 as of 2023-05-08 23:07:59
Size: 1005
Comment:
Revision 10 as of 2023-05-12 11:40:50
Size: 2304
Comment:
Deletions are marked like this. Additions are marked like this.
Line 29: Line 29:

=== Students from other universities ===
If you are not a student at TU and want to earn credit, you have to solicit [[https://www.tu.berlin/studierendensekretariat/themen-a-z/gast-und-nebenhoererschaft/|''Nebenhörerschaft'']]:

 * First fill the online [[https://www.static.tu.berlin/fileadmin/www/10002460/Bewerben_und_Einschreiben/Studierendenverwaltung/Antrag_auf_Nebenhoererschaft_englisch.pdf|''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 || #### || 3 || 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).

'''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. '''

Probabilistic Modling and Inference

General Information

Lecture

Tuesdays 14-16 (23.5.2023-)

Room

MAR 4.062

Teachers

Shinichi Nakajima

Contact

nakajima@tu-berlin.de

Language

English

Credits

3 ECTS, Elective Course in Machine Learning Module II (computer science M.Sc.)

ISIS

In preparation

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

    Probabilistic Modeling and Inference

    ####

    3

    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).

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.

IDA Wiki: Main/SS23_PMI (last edited 2023-06-06 18:23:07 by ShinichiNakajima)