BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Fernando E. Rosas (Faculty of Medicine\, Department of Brain Scien ces\, Imperial College) DTSTART:20220324T170000Z DTEND:20220324T180000Z DTSTAMP:20260423T003246Z UID:MPML/67 DESCRIPTION:Title: To wards a deeper understanding of high-order interdependencies in complex sy stems\nby Fernando E. Rosas (Faculty of Medicine\, Department of Brain Sciences\, Imperial College) as part of Mathematics\, Physics and Machine Learning (IST\, Lisbon)\n\n\nAbstract\nWe live in an increasingly interco nnected world and\, unfortunately\, our understanding of interdependency i s still limited. As a matter of fact\, while bivariated relationships are at the core of most of our data analysis methods\, there is still no princ ipled theory to account for the different types of interactions that can o ccur between three or more variables. This talk explores the vast and larg ely unexplored territory of multivariate complexity\, and discusses inform ation-theoretic approaches that have been introduced to fill this importan t knowledge gap.\n\nThe first part of the talk is devoted to synergistic p henomena\, which correspond to statistical regularities that affect the wh ole but not the parts. We explain how synergy can be effectively captured by information-theoretic measures inspired in the nature of high brain fun ctions\, and how these measures allow us to map complex interdependencies into hypergraphs. The second part of the talk focuses on a new theory of w hat constitutes causal emergence\, and how it can be measured from time se ries data. This theory enables a formal\, quantitative account of downward causation\, and introduces “causal decoupling” as a complementary mod ality of emergence. Importantly\, this not only establishes conceptual too ls to frame conjectures about emergence rigorously\, but also provides pra ctical procedures to test them on data. We illustrate the considered analy sis tools on different case studies\, including cellular automata\, baroqu e music\, flocking models\, and neuroimaging datasets.\n LOCATION:https://researchseminars.org/talk/MPML/67/ END:VEVENT END:VCALENDAR