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UID:DSC-19985
DTSTART;TZID=Europe/Berlin:20231019T110000
SEQUENCE:1697780435
TRANSP:OPAQUE
DTEND;TZID=Europe/Berlin:20231019T120000
URL:https://www.dresden-science-calendar.de/calendar/de/detail/19985
LOCATION:MPI-CBG\, Pfotenhauerstraße 10801307 Dresden
SUMMARY:Timme: Network Dynamics as an Inverse Problem --Detecting network s
 ize and topology from time series
CLASS:PUBLIC
DESCRIPTION:Speaker: Marc Timme\nInstitute of Speaker: Institute for Theore
 tical Physicsand Center for Advancing Electronics Dresden (cfaed)\, TU Dre
 sden \nTopics:\n\n Location:\n  Name: MPI-CBG (MPI-CBG Auditorium (big hal
 f))\n  Street: Pfotenhauerstraße 108\n  City: 01307 Dresden\n  Phone: +49
  351 210-0\n  Fax: +49 351 210-2000\nDescription: The dynamics of biologic
 al networks enables the function of a variety of systems\, including metab
 olic\, gene-regulatory and neural circuits. To date\, it remains unclear h
 ow to extract key features of networks if only time series data from (some
 ) units are available. Here we report on recent progress on detecting stru
 ctural features from observed dynamics. First\, we demonstrate how to iden
 tify the number N of dynamical variables making up a network -- arguably i
 ts most fundamental property -- from recorded time series of only a small 
 subset of n&amp\;lt\;N variables. Second\, we sketch approaches to uncover
  network topological features from observed nodal time series data. We dem
 onstrate first steps of applying the general theoretical methods developed
  to simulated models of biological and artifical systems.  This is work wi
 th Jose Casadiego\, Mor Nitzan\, Hauke Haehne\, Georg Boerner and others. 
  [1] Topical Review: Marc Timme &amp\;amp\; Jose Casadiego\,  J. Phys. A 4
 7:343001 (2014). [2] Casadiego et al.\, Nature Comm. 8:2192 (2017).  [3] N
 itzan et al.\, Science Adv. 3:e1600396 (2017). [4] Haehne et al.\, Phys. R
 ev. Lett. 122:158301 (2019).
DTSTAMP:20260612T232432Z
CREATED:20230623T053950Z
LAST-MODIFIED:20231020T054035Z
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