Seminars in 2019
Deterministic Sequential Monte Carlo for non-Gaussian elliptic problems
Sangeetika Ruchi, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands 2.09.0.1315:15 - 16:45
Sequential Monte Carlo methods (SMC) are typically stochastic. Ensemble Transform Particle filter (ETPF) is a deterministic SMC method. It, however,…
more ›Uniform estimates for particle filters
Pierre del Moral, INRIA, Bordeaux Research Center, University of Bordeaux, France 2.09.0.1410:15-11:45
This talk is concerned with the long time behavior of particle filters and Ensemble Kalman filters. These filters can be interpreted as mean field…
more ›Nash Equilibria for Stochastic Games with Singular Control.
Jodi Dianetti, Universität Bielefeld 2.9.2.2210:15-11:45
A singular stochastic control problem typically describes the situation in which
an agent has to choose optimally an irreversible strategy in order to…
Asymptotic equivalence for diffusion processes and the corresponding Euler scheme
Ester Mariucci, Universität Potsdam, SFB 1294, Germany 2.9.0.1410:15 - 11:15
When looking for asymptotic results for some statistical model, global asymptotic equivalence, in the Le Cam sense, often proves to be a useful…
more ›Assimilating data with outer probability measures
Jeremie Houssineau, University of Warwick, UK 2.9.2.2213:00 - 14:00
Although using probability distributions to model uncertainty is by far the most widely accepted approach, it does not come without inconveniences. A…
more ›Kabinettwatch: Wer wird was im Bundeskabinett?
Julia Fleischer, Universität Potsdam 2.09.0.1210:15 - 11:15
Talk by Julia Fleischer and Markus Seyfried
Das Projekt Kabinettwatch beschäftigt sich mit der Vorhersage der Zusammensetzung des Bundeskabinetts…
more ›An extension of Dobrushin's uniqueness criterion and applications to Gibbs point processes
Tanja Pasurek, Universität Bielefeld, Germany 2.09.0.1312:00
We extend the classical Dobrushin's uniqueness criterion to Markov random fields on general graphs and with single-spin spaces that need not be…
more ›Downscaling Data Assimilation Algorithm for Dissipative Evolution Models Employing Coarse Mesh Observables
Edriss Titi, Texas A&M University, USA 2.09.0.1210:15 - 11:15
One of the main characteristics of infinite-dimensional dissipative evolution equations, such as the Navier-Stokes equations and reaction-diffusion…
more ›Non–linear functionals preserving normal distribution and their asymptotic normality
Linda Khachatryan, Institute of Mathematics of the National Academy of Science of RA, Yerevan, Armenia 2.09.0.1312:00
We introduce sufficiently wide classes of non-linear functionals preserving normal (Gaussian) distribution and establish various conditions under…
more ›Probabilistic Linear Solvers
Jon Cockayne, University of Warwick, UK 2.14.0.2110:15 - 11:15
A fundamental task in numerical computation is the solution of large linear systems, and iterative methods are among the most widely used solvers for…
more ›Kalman-Wasserstein Gradient Flows
Franca Hoffmann, California Institute of Technology, USA 2.09.0.12/1310:15 - 11:15
We study a class of interacting particle systems that may be used for optimization. By considering the mean-field limit one obtains a nonlinear…
more ›Fully Hyperbolic Convolutional Neural Networks
Eldad Haber, The University of British Colombia, Canada 2.28.0.10810:15-11:15
Convolutional Neural Networks (CNN) have recently seen tremendous success in various computer vision tasks. However, their application to problems…
more ›Applied Data Assimilation: diabetes phenotyping/forecasting + hybrid machine learning approaches
Matthew Levine, California Institute of Technology, USA 2.09.0.1210:15 - 11:15
Methods from data assimilation, inverse problems, and machine learning have shown exciting potential for transforming biomedicine.
First, I will show…
more ›What is the Lagrangian for Nonlinear Filtering?
Prashant Mehta, University of Illinois, USA 2.28.0.10210:15 - 11:15
There is a certain magic involved in recasting the equations in Physics, and the algorithms in Engineering, in variational terms. The most classical…
more ›Stellar Astrophysics: the power of simultaneous high resolution stellar spectroscopy, polarimetry and velocimetry. - Rotation, activity and stellar magnetic fields in the A0 standard star Vega
Torsten Böhm, Université de Toulouse 2.9.0.1211:00 - 12:00
Neo-Narval at TBL/Pic du Midi (France) will be the first instrument working simultaneously in high resolution spectroscopy, polarimetry and…
more ›Ensemble Data Assimilation for Coupled Models of the Earth System
Lars Nerger, Alfred-Wegener-Institute, Helmholtz Centre for Polar and Marine Science, Bremerhaven, Germany 2.9.0.1210:15- 11:15
Coupled models simulate different compartments of the Earth system as well as their interactions. For example coupled ocean-biogoechemical models…
more ›Data assimilation for the stochastic one-layer rotating shallow water system driven by transport noise
Oana Lang, Imperial College London, UK 2.14.0.0910:15 -11:15
In this talk we will present a data assimilation problem based on a new stochastic rotating shallow
water (SRSW) signal and an adaptive tempering…
Regret analysis of the Piyavskii-Shubert algorithm
Sébastien Gerchinovitz, IRT Saint-Exupéry, Toulouse, France 2.12.0.01 (large Lecture hall)10:15 - 11:15
We consider the problem of maximizing a non-concave Lipschitz function f over a bounded domain in dimension d. In this talk we provide regret…
more ›Using data assimilation, systems physiology, and healthcare data to forecast physiology in an intensive care unit: why it is important, what is possible, what is hard, and the state of the art
David Albers, University of Colorado, USA 2.9.2.2215:00 - 16:00
Bayesian Inference Made Easy via Auxiliary Augmentations
Theo Galy-Fajou, Technische Universität Berlin 2.14.0.26/2712:30 - 14:00
Bayesian Inference is almost always a very challenging mathematical and computational problem. In the context of Gaussian Process, only a Gaussian…
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