The workshop will address computational and theoretical issues in stochastic modeling and model reduction in molecular and complex systems. In particular, the program will include topics ranging from quantum to mesoscale modelling, with focus on uncertainty quantification, machine learning and approximate inference method, methods using both quantum and classical models, ...

Stochastic differential equations are fundamental tools of modern mathematical modelling; they describe everything from the performance of financial instruments to atomic motion to the complex motion of fish schools or bird flocks. In recent years they have also been used increasingly as tools for the parameterization of artificial models such ...

This workshop brings together specialists working on various crossroads through conservative dynamics. It will highlight cutting edge research involving methods from symplectic topology, as well as interactions with other fields including smooth ergodic theory and PDEs.

The phenomenon of KPZ (Kardar-Parisi-Zhang) universality was a very active research area in the last 10 years. One can say that it describes universal statistical properties of long directed optimal paths (geodesics) in 2D disordered environment. Apart from many physical applications, it is remarkable for extremely strong universality properties in ...

The summer school will provide courses from experts in the areas of the scope of the program ''Dynamics with Structures''. It is intended to provide surveys of modern directions in the theory of dynamical systems on the level of graduate students and junior researchers. The goal is to propagate modern ...

This workshop brings together dynamicists who use techniques from, and are motivated by, combinatorics, geometry, and number theory.  The topics cover a broad swath of dynamics, including ergodic theory, homogeneous dynamics, symbolic dynamics, Teichmuller theory, and billiards, and the aim of the workshop is to highlight the common features across these subjects.

Functional data such as space curves, images, and surfaces are seldom sensed directly; curves are often noisily and discretely sampled, images are subject to blurring and deformation, and surfaces are often obtained via indirect linear measurements. Understanding the generation of the observations then requires modelling the act of acquisition, and ...

Spatio-temporal modelling central to many modern applications, but the dimensionality of the domain of such data poses both conceptual and computational statistical challenges. These are exacerbated in a nonparametric setting, where questions related to asymptotic framework and invariance assumptions arise. The areas of functional data analysis and random field analysis ...

Topological and discrete data such as trees and networks constitute strongly non-Euclidean structures, often beyond the reach of traditional statistical tools. Their analysis is often challenged by computational tractability, as natural constraints such as permutation invariance are computationally hard to implement. Still, such data can be often transposed into more ...

Important classes of functional data, such as random measures and random operators, are intrinsically constrained and need to be represented as elements of suitable non-Euclidean spaces, such as Hilbert manifolds. The interplay between the infinite dimensionality of their variation and the non-linearity of their representation space poses novel challenges for ...

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This conference contains contributions that give an overview of the current research in geometric mechanics. This scientific subject is simultaneously close to mathematics, physics, and engineering and its general philosophy consists in taking advantage of fruitful interactions between geometry on the one hand and dynamics and mechanics on the other. ...

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Transfer operators have been used to study rare and extreme events in dynamical systems and the linear - or nonlinear - response of systems to perturbations, including applications to climate dynamics.

This conference brings together experts from both theoretical and applied aspects of these studies, also in ...

This school will provide courses from experts on several aspects of the spectrum of transfer operators. Special attention will be provided to the theory of anisotropic spaces, and to applications in geometrical or physical settings.

The target audience includes PhD students and young postdocs. We plan 3 or 4 minicourses and ...

This conference brings together experts who study Ruelle-Pollicott resonances by using semiclassical and dynamical approaches.

Topics range from the Fried conjectures and other geometrical conjectures to various approaches to construct anisotropic spaces and strategies to obtain spectral gaps and essential spectral gaps, including the fractal uncertainty principle, and addressing non ...

There has recently been an explosion of results about transfer operators acting on anisotropic Banach spaces, starting with correlation decay and the analyticity properties of the Ruelle dynamical zeta function of uniformly hyperbolic maps and flows. These techniques have been extended to hyperbolic systems withsingularities, but the results there ...