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1
Workshop — Nonlinear Elasticity: Modelling of multi-physics and applications workshop
25 mar 2024 - 28 mar 2024 • ICMS, Bayes Centre, Edinburgh, Royaume-Uni
Organisateur:
ICMS - International Centre for Mathematical Sciences
Identifiant de l'évènement:
1593193
2
SSBF 2024 — Summer School on Bayesian filtering: fundamental theory and numerical methods
06 mai 2024 - 10 mai 2024 • ICMS, Bayes Centre, Edinburgh, Royaume-Uni
Organisateur:
ICMS - International Centre for Mathematical Sciences
Résumé:
The proposed summer school is devoted to the fundamental theory, state-of-the-art methodologies and real-world applications of Bayesian filtering, including sequential Monte Carlo (SMC) algorithms and other popular techniques, such as sigma-point methods for nonlinear Kalman filtering, Gaussian-mixture filters and others. We will introduce the basics of the field, so the summer school can be followed by an heterogenous audience. Basic notions on linear algebra, statistics, probability, and calculus are recommended. Then, the main targeted group for this summer school is PhD students with background in mathematics, statistics, physics, engineering, or computer science (but not only). Other students (e.g., last year MSc students) and early-career academics with similar background are also invited to apply. We intend to schedule 5 short courses (one-day tutorials) from renowned international researchers. These tutorials will cover the theoretical foundations of the field, current methodological trends, and relevant applications. Some courses may include hands-on sessions in (personal) computers. The target audience include researchers working on the field, as well as students aiming at being introduced to the topic.
Identifiant de l'évènement:
1593174
3
SMC 2024 — 6th Workshop on Sequential Monte Carlo Methods
13 mai 2024 - 17 mai 2024 • ICMS, Bayes Centre, Edinburgh, Royaume-Uni
Organisateur:
ICMS - International Centre for Mathematical Sciences
Résumé:
Sequential Monte Carlo (SMC) methods, also known as particle filters or particle methods, have become popular and powerful tools for computational inference in complex probabilistic models used in many and varied fields and applications. The research community includes practitioners and theoreticians at the intersection of statistics, computer science, electrical engineering, and applied mathematics. The interest in SMC methods have rapidly grown in the last decade, jointly with the new challenges and the enormous potential of SMC to tackle high-impact problems in applied sciences (e.g., meteorology, biomedicine, robotics, etc.).
Identifiant de l'évènement:
1593208
Sujets apparentés:


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Dernière mise à jour: 30 novembre 2023