Suchergebnis: Katalogdaten im Herbstsemester 2023

Rechnergestützte Wissenschaften Master Information
Kernfächer (fortgesetzt)
Höchstens eine der beiden Lerneinheiten
263-5210-00L Probabilistic Artificial Intelligence bzw.
252-0535-00L Advanced Machine Learning
darf als Kernfach angerechnet werden. Eine Anrechnung der anderen Lerneinheit in einer anderen Kategorie ist jedoch zulässig.
Für die Kategoriezuordnung wenden Sie sich an das Studiensekretariat (www.math.ethz.ch/studiensekretariat).
NummerTitelTypECTSUmfangDozierende
263-5210-00LProbabilistic Artificial Intelligence Information Belegung eingeschränkt - Details anzeigen W8 KP3V + 2U + 2AA. Krause
KurzbeschreibungThis course introduces core modeling techniques and algorithms from machine learning, optimization and control for reasoning and decision making under uncertainty, and study applications in areas such as robotics.
LernzielHow can we build systems that perform well in uncertain environments? How can we develop systems that exhibit "intelligent" behavior, without prescribing explicit rules? How can we build systems that learn from experience in order to improve their performance? We will study core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as robotics. The course is designed for graduate students.
InhaltTopics covered:
- Probability
- Probabilistic inference (variational inference, MCMC)
- Bayesian learning (Gaussian processes, Bayesian deep learning)
- Probabilistic planning (MDPs, POMPDPs)
- Multi-armed bandits and Bayesian optimization
- Reinforcement learning
Voraussetzungen / BesonderesSolid basic knowledge in statistics, algorithms and programming.
The material covered in the course "Introduction to Machine Learning" is considered as a prerequisite.
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