URPP Foundations of Human Social Behavior

 

Computational Neuroeconomics and Neuroscience

Instructor

Prof. Dr. Dr.med. Klaas Enno Stephan

Time and location

Wed, 15:00-16:30                 Room: BLU-E-003

Course description

This seminar covers a broad variety of mathematical and statistical methods used in contemporary computational neuroscience and neuroeconomics. This semester is devoted to machine learning techniques, many of which are promising tools for neural data analysis and the modeling of human learning and decision making. This semester we will cover a textbook entitled Pattern Recognition and Machine Learning (2007, corr. 2nd printing ed.) by Christopher M. Bishop. Each week a course participant will present one chapter of the book, which will be followed by general discussion. Most chapters contain more material than can be presented and discussed within 90 minutes, so presenters are encouraged to focus on a selection of ideas that can be presented in 45-60 minutes in order to allow for questions and discussion.

Credit points

3.0 ECTS

Language

English

Course registration

If you wish to attend this course, please send an e-mail with your name, address, telephone number, and student ID number (Matrikelnummer) to Tamara Herz.

Contact

Please send your suggestions for the course schedule or any feedback to Lars Kasper.

Course schedule

Date Topic Chapter
22-09-2010 Probability, Decision, and Information Theory 1
13-10-2010 Density Estimation, Bayesian Inference 2
20-10-2010 Linear Models for Regression 3
27-10-2010
Location: Seminarraum
Winterthurerstrasse WIH 03
Linear Models for Classification 4
03-11-2010 Kernel Methods I: Gaussian Processes 6
10-11-2010 Kernel Methods II: SVM and RVM 7
17-11-2010 Probabilistic Graphical Models 8
24-11-2010 Mixture Models and EM 9
01-12-2010 Approximate Inference I:
Deterministic Approximations
10
08-12-2010 Approximate Inference II:
Stochastic Approximations
11
15-12-2010 Inference on Continuous Latent Variables:
PCA, Probabilistic PCA, ICA
12
22-12-2010 Sequential Data: Hidden Markov Models,
Linear Dynamical Systems
13-113-2