Presentations
Here you can find the presentations from the SFB events such as Colloquia and Seminars. The presentations are being made available for the public with permission of the speakers.
Colloquia
2018

Approximate Kernel Embeddings of Distributions
Presentation by Dino Sejdinovic, University of Oxford, UK [PDF]

Numerical Analysis in Visual Computing: what we can learn from each other
Presentation by Uri Ascher, University of British Columbia, Canada [PDF]

The Epidemic Type Aftershock Sequence (ETAS) Model
Presentation by Maximillian Werner, University of Bristol, UK
2017

Distributional Uncertainty in Uncertainty Quantification
Presentation by Tim Sullivan, Zuse Institute Berlin and Freie Universität zu Berlin, Germany [PDF]

Comparing deep neural networks against humans: Object recognition with weak signals
Presentation by Felix Wichmann, Universität Tübingen, Germany [PDF]
Seminars
2018

On stability of a class of Kalman  Bucy filters for systems with nonlinear dynamics
Presentation by Toni Karvonen, Aalto University, Finland [PDF]

Composing stochastic quasiNewtonType algorithms
Presentation by Thomas Schön, Uppsala University, Sweden [PDF]

Localization for high dimensional data assimilation and MCMC
Presentation by Xin T. Tong, National University of Singapore, Singapore [PDF]
2017

Minimizationbased sampling from the posterior distribution for inverse problems
Presentation by Dean Oliver, Uni Centre for Integrated Petroleum Research, Bergen, Norway [PDF]

Modelling subsidence: On the use of the particle filter for geomechanical parameter estimation
Presentation by Femke Vossepoel, Delft University of Technology [PDF]

A class of nonlinear filters induced by local couplings
Presentation by Alessio Spantini, Massachusetts Institute of Technology (MIT), USA [PDF]
Kalman Lectures
2018

1st Kalman Lecture by Andrew Stuart
The first Kalman Lecture took place on the 24th of August 2018, where Andrew Stuart from Caltech talked about the "The Legacy of Rudolf Kalman".
Spring Schools
2018

David Dereudre  Lectures 1 and 2
Introduction to the Theory of Gibbs Point Process  Finite Volume Gibbs Point Process

David Dereudre  Lecture 3
Introduction to the Theory of Gibbs Point Process  Estimation of parameters

David Dereudre  Lecture 4
Introduction to the Theory of Gibbs Point Process

Youssef Marzouk  Lectures 1 and 2
Bayesian inference and MCMC foundations

Youssef Marzouk  Lecture 3
Bayesian modeling and computation for inverse problems

Youssef Marzouk  Lecture 4
Posterior approximations for Bayesian inverse problems

Youssef Marzouk  Lecture 5
Bayesian optimal experimental design

Carola Schönlieb  Lecture 1
Topics in Mathematical Imaging  Variational models & PDEs for imaging by examples

Carola Schönlieb  Lecture 2
Topics in Mathematical Imaging  Derivation of these models & analysis

Carola Schönlieb  Lecture 3
Topics in Mathematical Imaging  Numerical solution

Carola Schönlieb  Lecture 4
Topics in Mathematical Imaging  Some machine leaning connections