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Complex Systems Society (CSS)

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 CCS2023 in Salvador da Bahia, Brazil. 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 and is organized by SENAI CIMATEC.

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

CIRM – Centre International de Rencontres Mathématiques

A clear emphasis will be put on theoretical and numerical methods oriented towards applications in engineering and the sciences. Experts from applied mathematics will report on potential industrial applications, prototypes, and – where possible – existing use cases.

Mathématiques appliquées (en général),    Mathématiques numériques

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

Cours et évènements pour étudiants en mathématiques,    Calcul scientifique et science des données

Casa Matemática Oaxaca (CMO)

Large-scale, high-dimensional data sets are becoming ubiquitous in modern society, particularly in the areas of physical, biomedical, and social applications. For example, in the problem of predicting thyroid malignancy from biopsy images, the images are typically about 150,000 by 100,000 dimensions, which limit the application of many existing methods. There is an urgent need for accurate and efficient mathematical and statistical tools for the analysis and engineering of high-dimensional data sets. The proposed 5-Day workshop will bring researchers from different disciplines to collaboratively address the foundational computational and theoretical challenges in high-dimensional data analysis. The workshop is designed around the simple question ``how to accurately and efficiently process large-scale data in 10+ dimensions’’. Invited participants will review existing mathematical and statistical tools for high dimensional data sets, including the Monte Carlo methods, randomized algorithms, dimension reduction, sparse grid, network analysis, and interpolation-based deep neural networks, and compare their performance and address their limitations. The invited participants will collaboratively address the current challenges in high-dimensional data analysis, and design new strategies by combining existing tools and by introducing new methodologies for problems in 10+ dimensions.

Statistique, Théorie des jeux,    Mathématiques appliquées (en général)

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

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

Cours et évènements pour étudiants en mathématiques,    Réseaux, Internet

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

Calcul scientifique et science des données,    Théorie des graphes et combinatoire