Uncertainty Quantification in Engineering and Life Sciences

FS-2015

 

Course information: PDF

 

Lecturers

 

Prof. Dr. James L. Beck

Prof. Dr. Petros Koumoutsakos

Teaching Assistants

 

Dr. Stephen Wu

Dr. Panagiotis Angelikopoulos

Class Room

 

Tuesday: HG F 5 :15:00-17:00

Wednesday: HG F 5 :12:00-13:00

 

Office hour: C floor, CLT (Clausiusstrasse 33)

Thursday 10:00-11:00

Friday 10:00-11:00

Course Slides

Table of Contents

-------------------------

Lecture 1 - Sup. Material 1TA hour notes

Lecture 2 - Sup. Material 2, TA hour notes

Lecture 3 - Sup. Material 3, TA hour notes, MCS_notes, MCS_MATLAB

Lecture 4 - Sup. Material 4, TA hour notes

Lecture 5 - Sup. Material 5 (part 1, part 2), TA hour notes

Lecture 6 - Sup. Material 6, TA hour notes

Lecture 7 - (No Sup. Material), TA hour notes

Lecture 8 - Sup. Material 7+8 (example), TA hour notes, TA_MATLAB

Lecture 9 - Sup. Material 9, TA hour notes

Lecture 10 - Sup. Material 10, TA hour notes

Lecture 11 - Sup. Material 11, TA hour notes

Lecture 12 - Sup. Material 12, TA hour notes

Lecture 13 - Sup. Material 13 (extra 1, extra 2), no TA hour notes

Lecture 14 - no Lecture, no TA hour

 

Homework

Exercise 1 (due on September 29) - data

Exercise 2 (due on October 13)

Exercise 3 (due on October 27) - data

Exercise 4 (due on November 10) - data

Exercise 5 (due on November 24) - data

Exercise 6 (due on December 8) - data

 

*Note: all homework must be submitted before the end of the lecture

 


Useful Links

The intuitive inadequacy of classical statistics, Jaynes (1984)

Bayesian inference in astrophysics, Loredo (1990)

Bayesian system identification, Beck (2014)

 

Reference Books

Sivia, D.S. & Skilling, J., “Data Analysis: A Bayesian Tutorial 2nd Ed.,” Oxford University Press, 2006.

Jaynes, E.T., “Probability Theory: The Logic of Science,” Cambridge University Press, 2003. [Ch.1-3 available online for free]

Bishop, C.M., “Pattern Recognition and Machine Learning,” Springer, 2006.

(Click here to check status of books at the Computer Science Library)

 

MATLAB Tutorial

Summary of MATLAB tutorial (suggest watching the short videos)

PDF of Quick Start to MATLAB

Interactive Introduction by U. of Edinburgh (Youtube Video)

 

Elementary Topics on Probability Theory

Introduction from Pattern Recognition Ch.1

 

 

Last updated: 24/11/2015

[HW6 has been added at 12:30pm, 24/11/2015]