Big data and uncertainty quantification: statistical inference and information-theoretic techniques applied to computational chemistry

26 March - 03 April 2019
Organisers :
  • Carsten Hartmann
  • Fabio Nobile
  • Frank Pinski
  • Tim Sullivan

An incentive to use coarse-grained models is to use them for inference and control instead of the original (often intractable) model. Since coarse-grained models are always “wrong”, questions such as inference under model misspecification or goal-oriented uncertainty quantification (e.g. for control) come into play. This workshop will address such topics, with ...

Computational mathematics for model reduction and predictive modelling in molecular and complex systems

21 - 29 May 2019
Organisers :
  • Markos Katsoulakis
  • Benedikt Leimkuhler
  • Petr Plechac
  • Anders Szepessy
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, ...

Generalized Langevin Equations in classical and quantum simulations

04 - 14 June 2019
Organisers :
  • Sara Bonella
  • Carsten Hartmann
  • Simon Huppert

Conservative dynamics and its interactions

19 - 23 August 2019
Organisers :
  • Leonid Polterovich
  • Felix Schlenk

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.

by 31 Mar 2019

Bernoulli Lecture - Models of random growth and the Hamilton-Jacobi equation.

22 August 2019
Organisers :
  • Konstantin Khanin

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 ...

by 21 Aug 2019

Dynamical Systems - Summer School

26 - 30 August 2019
Organisers :
  • Jörg Schmeling

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 ...

by 31 Mar 2019

Dynamics, Geometry and Combinatorics

21 - 25 October 2019
Organisers :
  • Anders Karlsson
  • Bryna Kra
  • Omri Sarig
  • Jörg Schmeling

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.

by 31 May 2019

Low-dimensional and Complex Dynamics

02 - 06 December 2019
Organisers :
  • Magnus Aspenberg
  • Michael Benedicks
  • Jacek Graczyk
  • Feliks Przytycki
by 31 Jul 2019

Statistics for Indirectly Measured Functional Data

30 March - 03 April 2020
Organisers :
  • Merle Behr
  • Aurore Delaigle
  • Sofia Olhede
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 ...

Functional Data over Multidimensional Domains

27 April - 01 May 2020
Organisers :
  • John Aston
  • Anthony Davison
  • Shahin Tavakoli
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 ...

Statistics for Topological and Discrete Data

25 - 29 May 2020
Organisers :
  • Kathryn Hess Bellwald
  • Sofia Olhede
  • Katharine Turner
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 ...

Geometrical Statistics and Functional Data

22 - 26 June 2020
Organisers :
  • Ian Dryden
  • Simon Lunagomez
  • Victor Panaretos
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 ...