Probabilistic and statistical methods for networks

21 August - 1 September 2017
(arrival 20 August, departure 1 September)
Venue: Mathematics Building of TU Berlin

The summer school will focus on probabilistic and statistical methods for networks. This is an enormously rich topic that has many connections between branches of mathematics, and applications to many other scientific disciplines. The central theme is randomness that may arise in various forms: it can be used to construct models for networks, to analyse networks using statistical methods, or as part of stochastic processes on networks. One strand of the school will consider the theory of statistical physics models on networks; another strand will develop tools of statistical inference in network data; and a third strand investigates applications such as networks in neuroscience, traffic and telecommunication.

The School is primarily aimed at graduate students, but also to postdocs, working in applied probability or in one of the application fields with strong probabilistic flavour.

 

Speakers

Click for a summary and suggested reading

Shankar Bhamidi (North Carolina) - Probabilistic and statistical problems pertaining to dynamic networks
Lecture_1_Berlin_Bath_full.pdf / Lecture1-worksheet.pdf / Lecture_2_Berlin_Bath_Full.pdf / Lecture2-worksheet.pdf / Lecture_3_Berlin_Bath_full.pdf
Benedikt Jahnel (Berlin) - Stochastic geometry in telecommunications

Max Klimm (Berlin) - Selfish routing in networks

Peter Mörters (Bath) - Reinforced branching processes

Tiago Peixoto (Bath) - Statistical inference of network structure and dynamics

Jörg Polzehl - Connectivity networks in neuroscience - construction and analysis

Wilhelm Stannat (Berlin) - Stochastic mean-field theories for brain networks

Lenka Zdeborová (Saclay) - Inference on networks via cavity method and message passing

 



The schedule and further information.



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