Konferenzen  >  Mathematik  >  Komplexe Netzwerke

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Kurse und Veranstaltungen für Studenten der Mathematik,    Netzwerke, Internet

The Young Researchers community arranges an informal gathering designed for PhD students and early-career scientists. Attendees will be able to participate in talks delivered by distinguished researchers, gain insights into the scientific and life experiences of both junior and senior colleagues, and, of course, socialise and have fun.

As people learn to live with the SARS-CoV-2 virus, the way forward is increasingly being seen as a new normal. In this context that we have the pleasure of welcoming you to the next edition of the Conference on Complex Systems CCS2024 in Exeter, UK and the Warmup in London, from 29-30 August. The CCS is the largest and most important annual meeting of the international complex systems community. It comes under the auspices of the Complex Systems Society.

The international Traffic & Granular Flow Conference will gather an interdisciplinary audience working in the area of physics, computer sciences, engineering, granular, vehicular and pedestrian flow. It aims to give a global perspective on the latest developments and new ideas in the field of granular flow and urban mobility. The TGF scope will also include data-driven transport modelling, pedestrian and evacuation dynamics, collective animal behaviour, 3D animation, swarm behaviour and collective dynamics of other biological systems

data transport (internet traffic /cyber systems), pedestrian and evacuation dynamics, collective animal behaviour, 3D animation, swarm behaviour and collective dynamics of other biological systems

The International Conference on Complex Networks and their Applications aims to bring together researchers from different scientific communities working on network-related areas.

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