Yuansi Chen: Katalogdaten im Herbstsemester 2024 |
| Name | Herr Prof. Dr. Yuansi Chen |
| Lehrgebiet | Statistik |
| Adresse | Seminar für Statistik (SfS) ETH Zürich, HG G 15.1 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telefon | +41 44 632 58 32 |
| yuansi.chen@stat.math.ethz.ch | |
| Departement | Mathematik |
| Beziehung | Ausserordentlicher Professor |
| Nummer | Titel | ECTS | Umfang | Dozierende | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 401-3620-74L | Student Seminar in Statistics: MCMC Sampling Algorithms in Bayesian Computation  Number of participants limited to 24. Mainly for students from the Mathematics Bachelor and Master Programmes who, in addition to the introductory course unit 401-2604-00L Probability and Statistics, have heard at least one core or elective course in statistics. Also offered in the Master Programmes Statistics resp. Data Science. | 4 KP | 2S | Y. Chen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Through reading a series of research articles on Bayesian computation, we first review several basic types of posterior sampling problems that arise in Bayesian statistical inference. Then we discuss how tailored MCMC sampling algorithms were designed to provide efficient sampling for each type of problem, the intuition behind them and theoretical justifications of their computational complexity. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The main goal is for the students to get familiar with the basic types of posterior sampling problems that arise in Bayesian statistical inference and to understand the standard ways of designing MCMC sampling algorithms to tackle these problems. When faced with posterior sampling problems in Bayesian statistical inference in the future, the students will have a rough idea on what kind of sampling algorithms might be useful and efficient. The secondary goal is to acquire the theoretical tools to justify the computational complexity of those sampling algorithms. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kompetenzen |
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| 401-5620-00L | Research Seminar on Statistics | 0 KP | 1K | Y. Chen, N. F. Meinshausen, J. Peters, J. Ziegel, R. Furrer, L. Held, T. Hothorn, D. Kozbur, A. Sousa Bandeira, M. Wolf | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Research colloquium | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 401-5640-00L | ZüKoSt: Seminar on Applied Statistics | 0 KP | 1K | M. Kalisch, F. Balabdaoui, Y. Chen, R. Furrer, L. Held, T. Hothorn, L. Meier, N. F. Meinshausen, J. Peters, M. Robinson, F. Sigrist, A. Sousa Bandeira, C. Strobl, J. Ziegel | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Etwa 3 Vorträge zur angewandten Statistik. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Kennenlernen von statistischen Methoden in ihrer Anwendung in verschiedenen Anwendungsgebieten. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | In etwa 3 Einzelvorträgen pro Semester werden Methoden der Statistik einzeln oder überblicksartig vorgestellt, oder es werden Probleme und Problemtypen aus einzelnen Anwendungsgebieten besprochen. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Dies ist keine Vorlesung. Es wird keine Prüfung durchgeführt, und es werden keine Kreditpunkte vergeben. Nach besonderem Programm: http://stat.ethz.ch/events/zukost Lehrsprache ist Englisch oder Deutsch je nach ReferentIn. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 401-5680-00L | Foundations of Data Science Seminar | 0 KP | H. Bölcskei, Y. Chen, J. Peters, A. Sousa Bandeira, F. Yang | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Research colloquium | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||