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== 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 [[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''' || || 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. ''' |
Probabilistic Modling and Inference
General Information
Lecture |
Tuesdays 14-16 (23.5.2023-) |
Room |
MAR 4.062 |
Teachers |
Shinichi Nakajima |
Contact |
|
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
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.