[Comp-neuro] Reminder: Summer school on nonlinear methods, application deadline 10th of July

Michael von Papen vonpapen at geo.uni-koeln.de
Tue Jun 30 13:31:32 CEST 2015

Dear all,

This is a reminder for the upcoming Cologne Summer School on non-linear 
analysis methods for master's degree and PhD students. Deadline for 
applications is 10th of July, 2015.

Cologne Summer School 2015:
*Non-Linear Methods for Complex Systems Analysis*
Date: Mon-Fri 28.09-02.10.2015
Location: *University of Cologne*, Germany
This one-week summer school brings together *master's degree and PhD 
students from international universities* for an interdisciplinary 
hands-on learning experience. The workshop will introduce non-linear 
analysis methods using the Python toolbox pyunicorn. With the techniques 
presented in the summer school, such as complex networks and phase space 
concepts, the students will be able to characterize highly complex 
systems. Such systems are frequently encountered, e.g., in *biology, 
chemistry, economics, geoscience, neuroscience, and physics*. Lectures 
and computer labs will be led by Dr. Reik Donner and Marc Wiedermann 
from the Potsdam Institute for Climate Impact Research. For the complete 
program visit *complexsystems.uni-koeln.de/summerschool.html*. The 
application deadline is 10.07.2015. The summer school is organized by 
the Competence Area 3: Quantitative Modeling of Complex Systems of the 
University of Cologne. Contact: Dr. Michael von Papen 
(/vonpapen at geo.uni-koeln.de/)


The Competence Area 3: Quantitative Modeling of Complex Systems of the 
University of Cologne hosts a summer school to introduce novel and 
groundbreaking methods for the analysis of scientific data. For this 
matter, we bring together master's degree and PhD students from the 
University of Cologne and from international universities for an 
interdisciplinary learning experience. The aim of the summer school is 
not only to teach new analysis methods, but also to foster scientific 
collaboration and discussion between students of different fields of study.

This year, the summer school of the Competence Area 3 will introduce 
non-linear analysis methods to study highly complex systems, which 
cannot be sufficiently characterized with linear methods. Such systems 
are frequently encountered, e.g., in biology, chemistry, economics, 
geoscience, neuroscience, and physics. The one-week summer school will 
take place from Monday to Friday, September 28 - October 2, at the 
University of Cologne, Germany. The strongly interdisciplinary hands-on 
course consists of lectures and computer labs and will provide the 
students with novel analysis techniques and concepts. Amongst others, 
the workshop will cover topics such as detrended fluctuation analysis, 
complex networks, scaling analysis, synchronization, transfer entropy, 
and causality, which help to characterize systems that are governed by 
non-linear processes.

The summer school is led by *Dr. Reik Donner and Marc Wiedermann* from 
the *Potsdam Institute of Climate Impact Research* based on their 
lectures at the Humboldt University, Berlin, and their popular 
short-courses at the European Geosciences Union General Assembly. They 
will introduce the Python toolbox /pyunicorn/ for non-linear analysis 
along with prominent examples of modern analysis frameworks highlighting 
the methodological variety of complex systems based data analysis (see 
program below). The techniques that are taught in the summer school will 
be illustrated by applications to real-world data from different fields 
of study.

The course materials will be made available to the participants after 
the course, including example codes for the platform-independent 
open-source software Python and the toolbox pyunicorn. The course will 
be held in English.

For questions, please contact Mitch von Papen (vonpapen at geo.uni-koeln.de).


The summer school consists of approximately the same amount of lectures 
and computer labs. During the lectures, the basics of the analysis 
methods are explained. Subsequently, these methods are applied to 
synthetic and real-world data in computer labs. The students work on a 
project in small groups and present and discuss their results at the end 
of the workshop.

The students are introduced to the concepts of several non-linear 
analysis methods and will gain experience in applying the toolbox 
pyunicorn as well as in interpreting the results. Ideally, the summer 
school will enable the students to use the learned techniques on their 
own scientific data after the summer school. The approximate schedule 
for the summer school is given below. Note however, that changes may 
occur due to group dynamics.

  /Monday, September 28th/

09:00 a.m. | Lecture 1: Introduction - linear vs. non-linear methods, 
Stationarity, uni- and multivariate correlation analysis, classical 
early warning methods, non-linearity tests and surrogate data
11:00 a.m. | Lecture 2: Long-range dependence and scaling analysis, 
Persistence and anti-persistence, power spectrum, Hurst exponent, 
detrended fluctuation analysis
02:00 p.m. | Tutorial 1: Introduction to Python, Why Python in science?, 
important packages for scientific computing, common data types, 
structure of pyunicorn
04:00 p.m. | Tutorial 2: Assignment of group projects, (6 groups a 5 
07:00 p.m. | Social get-together at local brewery

  /Tuesday, September 29th/
09:00 a.m. | Lecture 3: Introduction to complex networks, Mathematical 
representation of networks, structural network characteristics, basic 
network models, identification of power-laws, interconnected and 
multi-layer networks
11:00 a.m. | Lecture 4: Inferring networks from data, Functional network 
analysis (correlation networks, examples from climatology, 
neurophysiology and economics), visibility graphs
02:00 p.m. | Tutorial 3: tbd
04:00 p.m. | Tutorial 4: tbd

  /Wednesday, September 30th/

09:00 a.m. | Lecture 5: Information theory and entropy, Basic concepts, 
Shannon-, Renyi- and Tsallis-entropies as statistical quantifiers, 
Kolmogorov-Sinai (source) entropy and estimation via block entropies, 
order patterns and permutation entropy, mutual information, transfer 
entropy and causality, independent component analysis
11:00 a.m. | Lecture 6: Synchronization, Definition and types of 
synchronization, phase synchronization: order parameters and phase 
dynamics from data, generalized synchronization
02:00 p.m. | Tutorial 5: tbd
04:00 p.m. | Tutorial 6: tbd

  /Thursday, October 1st/

09:00 a.m. | Lecture 7: Phase space concepts, Phase space of dynamical 
systems, embedding, fractal dimensions, correlation integral and 
relation with entropies, entropy estimates from embedded data
11:00 a.m. | Lecture 8: Recurrence analysis, Recurrence in phase space; 
recurrence plots, quantification analysis and networks; multivariate 
generalizations; applications: synchronization analysis, coupling direction
02:00 p.m. | Tutorial 7: tbd
04:00 p.m. | Tutorial 8: tbd

  /Friday, October 2nd/

09:00 a.m. | Presentation and discussion of projects 1-3 from the tutorials
11:00 a.m. | Presentation and discussion of projects 4-6 from the tutorials
02:00 p.m. | Open discussion: Outlook on contemporary developments in 
the field
03:30 p.m. | End of day 5: Farewell

Institute of Geophysics & Meteorology

Coordinator of Competence Area III:
Quantitative Modeling of Complex Systems

Dr. Michael von Papen
Pohligstr. 3 (R 3.224)
50969 Cologne

Tel.: +49 (0)221 470-2841
Email: vonpapen at geo.uni-koeln.de

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