Konferenzen  >  Mathematik  >  Komplexe Netzwerke

Simons Laufer Mathematical Sciences Institute (SLMath)

In a growing number of applications, one needs to analyze and interpret data coming from massive networks. The statistical problems arising from such applications lead to important mathematical challenges: building novel probabilistic models, understanding the possibilities and limitations for statistical detection and inference, designing efficient algorithms, and understanding the inherent limitations of fast algorithms. The workshop will bring together leading researchers in combinatorial statistics, machine learning, and random graphs in the hope of cross-fertilization of ideas.

combinatorial statistics, random graphs, network inference, network reconstruction, detection, estimation

Wissenschaftliches Rechnen und Datenwissenschaft,    Graphentheorie und Kombinatorik

Banach Center

This meeting aims to gather top-notch specialists in the field of dynamical systems on networks to discuss differences and similarities in the approaches based on optimal transport, gradient flows, and operator theory. At the conference, the most recent topics such as co-evolving networks, multi-scale analysis, control theory, and applications will also be addressed.