CS-E407516 - Special Course in Machine Learning, Data Science and Artificial Intelligence D: Tractable Probabilistic Modelling, Lectures, 28.4.2023-2.6.2023

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

The aim of the course is to provide an introduction to the field of tractable probabilistic models and highlight active research directions in the field (with a focus on probabilistic circuits).

Credits: 3

Schedule: 28.04.2023 - 02.06.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Martin Trapp, Arno Solin

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Students need to apply with a motivation letter.

    Recommended for Doctoral students.

    Each student presents one paper and acts as an opponent to one selected paper presented by a fellow student. Attendance and active participation in the discussions are mandatory.

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