# All Seminars

### Adaptive convergence results for numerical efficient Bayesian methods

Jan van Waaj, University of Amsterdam, Netherlands 2.28.0.108

### Minimization-based sampling from the posterior distribution for inverse problems with Gaussian prior distributions

Dean S. Oliver, Uni Centre for Integrated Petroleum Research, Bergen, Norway 2.09.0.1410:15-11:45

Inverse problems for subsurface ow are typically characterized by large numbers of para- meters (e.g. coef cients of PDEs describing ow and transport)…

more ›### Phase transition in mean-field games: An application to synchronization of coupled oscillators

Prashant Mehta, University of Illinois at Urbana-Champaign, USA 2.09.014Begin: 14:00

This talk is concerned with phase transition and self-organization in mean-field games.

The motivation comes from the following sequence of events…

more ›### Improving Data Assimilation by Surfing the Waves

Juan Restrepo, Oregon State University, USA 2.28.2.12310:15-11:45

The use of models and data, via data assimilation, is one ofthe strategies pursued to improve climate and weather predictions and retrodictions. In…

more ›### On the use of the particle filter for geomechanical parameter estimation when monitoring subsidence due to hydrocarbon extraction

Femke Vossepoel, Delft University of Technology, Netherlands 2.28.0.10410:15-11:15

Fluid extraction from a subsurface hydrocarbon reservoir results in compaction of the reservoir, in particular cases leading to subsidence and induced…

more ›### A class of nonlinear filters induced by local couplings

Alessio Spantini, Massachusetts Institute of Technology (MIT), USA 2.28.0.10410:15-11:15

We introduce a class of structure-exploiting nonlinear filters for high-dimensional state-space models with intractable transition kernels. The idea…

more ›### Generative Deep Learning

Sebastian Stober, University of Potsdam 2.28.0.104

A short introduction into Deep Learning will be followed by an overview on Deep Generative Models. This will include energy based models (Boltzmann…

more ›### Multi-stability & Fixational Eye Movements: an energy potential modeling approach

Kevin Parisot, GIPSA-Lab Grenoble 2.14.4.15/1610:15 - 11:45

### Financial Market History: Reflections on the Past for Applied Mathematician today

Nicole El Karoui, Ecole Polytechnique, France 2.9.0.129:15 - 10:15

After World War II, the Bretton Woods Conference designed a new international

monetary order, establishing the supremacy of the dollar, while…

### Minimax optimality in Robust Detection of disorder times in Doubly Stochastic Poisson Process

Nicole El Karoui, Ecole Polytechnique, Franc 2.9.0.1210:45 - 11:45

We consider the minimax quickest detection problem of an unobservable time of proportional

change in the intensity of a doubly-stochastic Poisson…

### Machine Learning for Sensor Fusion in Positioning and Navigation

Arno Solin, Aalto University, Finland 2.28.0.10410:00 - 11:00

Low-cost and noisy sensor sources in modern smartphones introduce both interesting possibilities for new applications, and challenges for inference…

more ›### Data Assimilation in Autonomous Vehicles

Erin Linebarger, University of Utah, USA 2.28.0.10411:00 - 12:00

Guidance of autonomous vehicles (AVs) poses different challenges for data assimilation methods than geophysical applications, requiring novel…

more ›### Improving MCMC samplers with spectral theory and optimal transport

Nikolas Nüsken, Imerpial College London, UK 2.28.0.10410:15-11:45

Markov Chain Monte Carlo methods are popular tools in Bayesian statistics and molecular dynamics to draw samples from a given probability…

more ›### On stability of a class of Kalman - Bucy filters for systems with non - linear dynamics

Toni Karvonen, Aalto University, Finland 2.28.0.10410:15-11:15

This talk discusses stability of a class of Kalman-Bucy filters (including the classical extended Kalman-Bucy filter) for continuous-time systems with…

more ›### Composing stochastic quasi-Newton-Type algorithms

Thomas Schön, Uppsala University 2.28.0.10413:00 - 14:00

In this talk I will focus on one of our recent developments where we show how the Gaussian process (GP) can be used to solve stochastic optimization…

more ›### The Intrinsic Geometry of Scale - Free Networks

Tobias Friedrich, Hasso Plattner Institute 2.09.0.1310:15-11:15

The node degrees of large real-world networks often follow a power-law distribution. Such scale-free networks can be social networks, internet…

more ›### Thermodynamic limit and phase transitions in non-cooperative games: some mean-field examples

Paolo dai Pra, University of Padua 2.09.0.1316:15 - 17:45

In stochastic dynamics inspired by Statistical Mechanics the interaction between different particles, or agents, is usually …

### A nonparametric estimation problem for linear SPDEs

Randolf Altmeyer/ Markus Reiß, HU Berlin WIAS, Erhard-Schmidt Hörsaal, Mohrenstraße 39, 10117 Berlin10:00 - 12:30

It is well-known that parameters in the drift part of a stochastic ordinary differential equation, observed continuously on a time interval [0, T ],…

### Measures for diffusion, ergodicity & ageing

Ralf Metzler, Universität Potsdam 2.09.0.1310:15 - 11:45

After a short introduction into the history of Brownian motion I will present

the stochastic motion in several physical systems, in particular with…

### Parameter estimation problems for parabolic SPDEs

Igor Cialenco, Illinois Institute of Technology Weierstrass-Institute for Applied Analysis and Stochastics, Erhard-Schmidt-Hörsaal, Mohrenstraße 39, 10117 Berlin10:00 -12:30

In the first part of the talk we will discuss the parameter estimation problem using Bayesian approach for the drift coefficient of some linear …

more ›### Overview on stochastic models, McKean-Vlasov dynamics and their applications

Jean-Francois Jabir, National Research University Higher School of Economics, Moscow, Russia

This seminar aims to give a broad and straightforward presentation on fundamental aspects related to the theory and application of continuous-time…

more ›### Finite or infinite predictability horizon?

Tsz Yan Leung, University of Readings, UK 2.09.0.1310:15-11:00

It is well-accepted that the chaotic nature of atmospheric dynamics imposes an inherent finite limit of predictabil- ity. The idea originated from a…

more ›### Balancing robustness and accuracy in high resolution hydrological models

Sabine Attinger, Universität Potsdam 2.09.0.1310:15-11:45

Anthropogenic warming is anticipated to impact the hydrological cycle tremendously in the future. However, projections are accompanied by large…

more ›### Entropic and optimal transport

Christian Léonard, Université Paris Nanterre 2.09.2.2217:15

The Schrödinger problem is an entropy minimization problem on a set of path measures with prescribed initial and final marginals. It arises from a…

more ›### Localization for high dimensional data assimilation and MCMC

Xin Tong, National University of Singapore 2.09.0.1310:15 - 11:45

High dimensionality often appears in data assimilation and Bayesian sampling problems. It is prohibitive for most classical computational…

more ›### Integrated approaches to investigate reactive transport processes in soil and groundwater

Irina Engelhardt, Technische Universität Berlin 2.09.0.1210:15 - 11:45

The presentation gives an overview about experimental and numerical approaches to analyze reactive transport processes in soils and groundwater.…

more ›### Postponed due to illness- Kabinettwatch: Wer wird was im Bundeskabinett?

Markus Seyfried, Universität Potsdam, Germany 2.9.0.1410:15 - 11:45

This talk is postponed due to illness. The new date will be announced under events.

Dieser Vortrag wird krankheitsbedingt leider nicht statt finden.…

more ›### Talk moved to Friday, 09.11. 10:15 am - Image-based modelling of problems in cell motility

Till Bretschneider, The University of Warwick, UK 2.28.2.12310:15 -11:45

*This talk has been moved to Friday, the 09.11. at 10:15 in lecture hall 0.108, building 28, Campus Golm.*

Mathematical modelling has been key to…

more ›### Hamiltonian Monte Carlo methods on Hilbert spaces

Jakiw Pidstrigach, University of Bonn 2.9.0.1410:15 - 11:00

When sampling measures on Hilbert spaces one option is to first discretize the space and then apply standard Markov Chain Monte Carlo methods. This…

more ›### A Causal approach to spring-to-summer climate variability in the Southern Hemisphere

Elena Saggioro, University of Reading, UK 2.9.0.1411:00 - 11:45

The coupling between stratospheric and tropospheric dynamics is currently a topic of major interest [1,2]. In the context of the Southern…

more ›### Dances with Drones: Using Google’s TFLite for Autonomous Control of Aerial Drones by Gesture Recognition

Erin Linebarger, University of Utah (US) and SFB 1294, University of Potsdam 2.9.0.1410:15 - 11:45

Scientific app development for implementing robotics controllers and machine learning algorithms has become much easier with the introduction of tools…

more ›### Hawkes Processes with Sigmoid Gaussian Excitations

César Ojeda, Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS 2.9.0.1411:00 - 11:45

We propose a Hawkes point process model for point processes where the excitations are modulated via a Gaussian process prior with a sigmoid link…

more ›### Neural Particle Filter and Beyond

Simone Surace, University of Zürich, ETH Zürich and University of Bern, Switzerland 2.9.0.1410:15 - 11:00

Perception can be seen as unconscious inference in a dynamically changing environment and formalized as nonlinear Bayesian filtering. A heuristic…

more ›### FEAT: Fixation control by Evidence Accumulation to Threshold

Casimir Ludwig, University of Bristol 2.14.4.06/0716:15

Models of eye movement control differ in the extent to which fixation duration is controlled directly by…

more ›### Validity of linear response theory in high-dimensional deterministic dynamical systems

Caroline Wormell, University of Sydney and SFB visiting PhD research fellow 2.09.0.1310:15-11:45

Many physical problems, most importantly the quantification of climate change, involve estimating the response of a deterministic chaotic dynamical…

more ›### 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…

more ›### Advancements in Hybrid Iterative Methods for Inverse Problems

Julianne Chung, Virginia Tech 2.29.0.25/0.2610:00 - 11:00

n many physical systems, measurements can only be obtained on the exterior of an object (e.g., the human body or the earth's crust), and the goal is…

more ›### Challenges in Dynamical Systems Inference: New Approaches for Parameter and Uncertainty Estimation

Matthias Chung, Virginia Tech 2.29.0.25/0.2611:00 - 12:00

Mathematical modeling has been a key tool in various scientific fields (such as biology, medicine, and engineering) in understanding systems dynamics.…

more ›### Data-driven reconstruction of chaotic dynamics using data assimilation and machine learning

Marc Bocquet, École des Ponts ParisTech, France 2.26.0.7610:15 - 11:15

Recent progress in machine learning has shown how to forecast and, to some extent, learn the dynamics of a model from observations, resorting in…

more ›### Implicit equation-free methods applied on noisy slow-fast systems

Anna Dittus, Universität Rostock TU Berlin Mathematikgebäude Raum MA74814:15 - 15:15

Slow-fast systems consist of slow macroscopic and fast microscopic dynamics. By using equation-free methods, one can do a complete bifurcation…

more ›### Posterior Inference for Sparse Hierarchical Non-stationary Models

Lassi Roininen, University of Oulu, Finland 2.9.0.1310:00 - 11:00

Gaussian processes are valuable tools for non-parametric modelling, where typically an assumption of stationarity is employed. While removing this…

more ›### Statistics for chaotic dynamics and random patterns

Heikki Haario, LUT University (Technische Universität Lappeenranta), Finland 2.9.0.1311:00 - 12:00

We discuss methods for creating Gaussian likelihoods for data that does not directly follow any known statistics. Obvious summary statistics are…

more ›### Contaminant dispersal, numerical simulation, and stochastic PDEs

Tony Shardlow, University of Bath, UK 2.9.0.1213:00 - 14:00

Atmospheric dispersal of contaminants such as ash can be modelled by stochastic differential equations coupled to a large-scale weather model. We…

more ›### Multilevel ensemble Kalman filtering algorithms

Hakon Hoel, RWTH Aachen 2.9.0.1310:15 - 11:15

The ensemble Kalman filter (EnKF) is a Monte-Carlo-based sequential filtering

method that is often both robust and efficient, but its performance may…

### Relaxation techniques for PDE-constrained optimization in inverse problems

Tristan van Leeuwen, Universiteit Utrecht, The Netherlands 2.9.0.1310:15 - 11:15

PDE-constrained optimization problems arise in many applications, including inverse problems and optimal control. As optimization over both the…

more ›### -Cancelled- Convergence rates for optimised adaptive importance samplers

Ömer Deniz Akyıldız, Universtiy of Warwick 2.09.0.1310:15 - 11:15

-Cancelled-

Adaptive importance samplers are adaptive Monte Carlo algorithms to estimate expectations with respect to some target distribution which…

more ›### Some thoughts and questions towards a statistical understanding of DNNs

Ingo Steinwart, Universität Stuttgart online10:00 - 12:00

So far, our statistical understanding of the learning mechanisms of deep neural networks. (DNNs) is rather limited. Part of the reasons for this lack…

more ›### Regulation of Intracellular Signaling via Cellular Morphology

Meghan Driscoll , University of Texas Southwestern Medical Center, US online5:00 - 6:00 pm

Signaling is governed not only by the expression levels of molecules, but by their localization via mechanisms as diverse as compartmentalization in…

more ›### Mini seminar series on „Non-Gaussian large scale Bayesian inversion“

Jarkko Suuronen, Sahani Pathiraja, Teemu Härkönen, LUT and UP online12:00 - 13:30

jointly organised by Jana de Wiljes and the Lappeenranta-Lahti University of Technology (LUT, Finland) more ›

### Bayesian inference in machine learning

Vladimir Spokoiny, WIAS Berlin online10:00 - 12:00

Statistical inference for binary data is one of the central problem in machine learning which can be treated within a nonparametric Bernoulli model.…

more ›### Global sensitivity analysis in environmental modeling

Kim Aleksandra, ETH Zürich and Paul Scherrer Institute, Switzerland online10:15 -11:15

In today’s complex world and economy, international supply chains of goods cause global environmental impacts. Life Cycle Assessment (LCA) is a well…

more ›### Analysis of stochastic gradient descent in continuous time

Jonas Latz, University of Cambridge, UK online10:15 - 11:15

Stochastic gradient descent is an optimisation method that combines classical gradient descent with random subsampling within the target functional.…

more ›### Stability of UQ and Bayesian inverse problems

Bjoern Sprungk, TU Bergakademie Freiberg online10:15 - 11:15

For partial differential equations with random coefficients we investigate the sensitivity of the distribution of the random solution with respect to…

more ›### Theoretical perspectives on actin waves

Arik Yochelis, Ben-Gurion University of the Negev, Israel 2.28.0.10810:15 - 11:45

tba

invited by Carsten Beta

more ›### On recently developed non-Gaussian priors and sampling methods with application to industrial tomography

Lassi Roininen, Technische Universität Lappeenranta, Finland 2.14.0.2110:15 - 11:15

We consider two sets of new priors for Bayesian inversion and machine learning: The first one is based on mixture of experts models with Gaussian…

more ›### Gaussian likelihoods for ’intractable’ situations

Heikki Haario, Technische Universität Lappeenranta, Finland 2.28.0.108 (Campus Golm, building 28, room 0.108)10:00 - 11:00

Various modelling situations – including chaotic dynamics, stochastic differential equations, random patterns such as produced by the Turing…

more ›### Some statistical inference results for interacting particle models in a mean-field limit

Marc Hoffmann, Université Paris-Dauphine, France hybrid event, in person at WIAS (please register) and online; please contact Andrea Fiebig (fiebig[at]math.hu-berlin.de) for details10:00 - 12:00

We propose a systematic | theoretical | statistical analysis for systems of interacting

diffusions, possibly with common noise and/or degenerate…

### A modified discrepancy principle to attain optimal rates under white noise

Tim Jahn, Universität Bonn, Germany HU, Johann von Neumann-Haus (Rudower Chaussee 25), room: 3.00813:15 - 14:45

We consider a linear ill-posed equation in the Hilbert space setting under white noise. Known convergence results for the discrepancy principle are…

more ›### Parameter Estimation for Semilinear Stochastic Partial Differential Equations

Gregor Pasemann, Humboldt-Universität zu Berlin online via zoom, please contact Prof. S. Reich for the link10:15 - 11:15

A theory of parametric inference for semilinear stochastic partial differential equations is developed, with special emphasis put on diffusivity…

more ›### A duality formulation for filter stability

Jin Won Kim, University of Illinois at Urbana-Champaign, USA online via Zoom, pls contact Wilhelm Stannat if you would like to join16:15

In this talk, I revisit the problem of filter stability based on certain dual optimal control-type reformulations of the nonlinear filtering problem.

…

### Hypothesis testing on high-dimensional spheres: the Le Cam approach

Davy Paindaveine, Univerité libres de Bruxelles, Belgium hybrid, online- please contact Andrea Fiebig (HU) for the zoom link10:00 - 12:00

Hypothesis testing in high dimensions has been a most active research topics in the last

decade. Both theoretical and practical considerations make it…

### Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC

Torben Sell, University of Edinburgh, Scotland online, please contact us beforehand if you would like to join10:15 - 11:30

I will discuss a new neural network based prior for real valued functions on ℝ^d. The new prior is a Gaussian neural network prior, where each weight…

more ›### On the duality for nonlinear filtering

Jin W. Kim, University of Illinois at Urbana-Champaign, USA Campus Golm, Building 9, Room 2.2210:00 - 11:30

In this talk, I will present the dual control system for the hidden Markov model (HMM). This is a direct extension of classical duality between…

more ›### "Stochastic gradient descent in continuous time: discrete and continuous data" and "Augmenting Bayesian inference with possibility theory"

Jonas Latz (Heriot-Watt University, Edinburgh) & Jeremie Houssineau (University of Warwick, UK) Campus Golm, Building 5, Room 1.1010:00-12:00

**Jonas Latz:**

Optimisation problems with discrete and continuous data appear in statistical estimation, machine learning, functional data science,…

more ›### Stochastic Modelling with few Parameters

Philipp Meyer, UFS Data-centric Sciences, University of Potsdam Campus Golm, Building 9, Room 0.1210:15-11:15

Simple stochastic models can describe the fluctuations of a time series. A good way to get a first impression of the data is to look at the mean…

more ›### Toward a unified framework for large scale imaging problems: Theory, applications, and potential issues

Hossein S. Aghamiry, Université Côte d'Azur, Geoazur, Valbonne, France Campus Golm, Building 9, Room 1.1012:15-13:15

Visualizing and quantifying the properties of a medium using sparse indirect measurements is the final goal of all the imaging methods in different…

more ›### Learning in High-Dimensional Feature Spaces Using ANOVA-Based Fast Matrix-Vector Multiplication

Theresa Wagner, TU Chemnitz Campus Golm, building 9, room 0.1716:00-17:00

Kernel matrices are crucial in many learning tasks and typically dense and large-scale. Depending on the dimension of the feature space even the…

more ›### IRTG Workshop - Good Scientific Practice

Dr. Peter Schröder Campus Golm, building 29, room 0.25/0.2610:00-17:00

This workshop is part of the SFB IRTG Certificate Program and will be held by Dr. Peter Schröder. The onsite workshop wil deal with Good Scientif…

more ›### "Two prior models for edge-preserving Bayesian inversion" & "Geometry Parameter Estimation for Sparse X-ray Log Imaging"

Felipe Uribe & Angelina Senchukova, LUT University, Finland Campus Golm, building 9, room 1.2210:15 - 11:15

**Abstract by Felipe Uribe:**

In inverse problems arising in imaging science characterization of sharp edges in the solution is desired. Within the…

more ›### 'Projected Particle Filtering' and 'On ensemble size in a particle method for subsidence estimation'

Svetlana Dubinkina (VU Amsterdam) and Femke C. Vossepoel (TU Delft) Campus Golm, building 9, room 1.2210:00 - 11:00

**Abstract by Svetlana Dubinkina:**

Data assimilation of high-dimensional nonlinear models is subject to curse of dimensionality. It is when an ensemble…

more ›### Bayesian and Deterministic Spatio-Temporal Methods with Edge-Preserving Priors for Inverse Problems

Mirjeta Pasha, Tufts University, US Campus Golm, building 9, room 1.1012:13 - 13:15

Inverse problems are ubiquitous in many fields of science such as engineering, biology, medical imaging, atmospheric science, and geophysics. Three…

more ›### Hurst index estimation for SPDEs

Pavel Kriz, Charles University HU Berlin (Rudower Chaussee 25, room: 3.008)13:15 - 17:45

Hurst index determines regularity, self-similarity and autocovariance structure of a fractional Brownian motion (fBm). Although there is a vast…

more ›### IRTG Workshop: Presentation Skills for Science and Research (Part I - online)

Peter Schröder, brain4hire online10:00 - 17:00

This workshop on Presentation Skills for Science and Research will be held by Dr. Peter Schröder and is mandatory for Doctoral researchers of our…

more ›### IRTG Workshop: Presentation Skills for Science and Research (Part II )

Peter Schröder, brain4hire 2.29.0.25/0.26

This is Part II of the workshop 'Presentation Skills for Science and Research' and held by Dr. Peter Schröder. This workshop day is splitted in 3…

more ›### Hurst index estimation for SPDEs - seminar with Pavel Kriz

Pavel Kriz, Charles University, CZ 2.29.025/0.2613:30

Fractional Brownian motion (fBm) has been considered as a stochastic process generating autocorrelated (colored) Gaussian noise in various stochastic…

more ›### Reduced Basis Methods: From Key Ingredients to 4DVar

Martin Grepl, RWTH Aachen 2.9.0.1410:15 - 11:30

The reduced basis method is a certified model order reduction technique for the rapid and reliable solution of parametrized partial differential…

more ›### Networking Meeting

2.29.0.25/0.2610:15 - 11:45

Our CRC Networking Meeting with Karen Veroy-GRepl and Martin Grepl provides a chance to talk about career, chances, and the challenges for couples in…

more ›### From excitability to waves and back: Patterns related to subcritical finite wavenumber Hopf bifurcations

Arik Yochelis, Ben-Gurion University of the Negev, Israel 2.28.0.10810:15 - 11:30

Dissipative nonlinear waves arise in many systems that comprise non-equilibrium properties, such as action potentials, calcium waves,…

more ›### Kernel matrices in the flat limit

Simon Barthelmé, CNRS, Gipsa-lab 2.9.0.1316:15-17:15

*Simon Barthelmé (CNRS, Gipsa-lab), joint work with K. Usevich, N. Tremblay, P.-O. Amblard*

Kernel matrices are ubiquitous in statistics, numerical…

### IRTG Workshop: Mental Health (Part I)

Dr. Andrea Szameitat Online09:00 - 12:30

**First session (07.12.; 09:00 - 12:30) **

In the first session, this workshop focuses on what mental health is, what widespread mental health issues…

more ›### IRTG Workshop: Mental Health (Part II)

Dr. Andrea Szameitat Online09:00 - 12:30

**Second session (08.12.; 09:00 - 12:30)**

The second session focuses on the concept of resilience: what exactly is it, how does it serve us and how can…

### IRTG Workshop: Mental Health (Part III)

Dr. Andrea Szameitat Online19:00 - 21:00

**Third session (12.12.; 19:00 - 21:00)**

In this meeting you reflect together about your progress/current situation in an informal setting.

more ›

### Computing Spectra of Infinite-dimensional operators - what do we need?

Catherine Drysdal, University of Birmingham 2.9.2.2212:15 - 13:30

In this talk, I look at two examples regarding the numerical computation of spectra for infinite-dimensional non-self-adjoint operators. Two…

more ›### IRTG Workshop: Conflict Management (Part I)

Anna Royon-Weigelt2.29.0.25/0.2610:00 - 18:00

Date: February 8th & 9th, 2024

The workshop with Anna Royon-Weigelt covers basic aspects of communication, especially in intercultural contexts and…

more ›### IRTG Workshop: Conflict Management (Part II)

Anna Royon-Weigelt2.29.0.25/0.2610:00 - 18:00

The workshop with Anna Royon-Weigelt covers basic aspects of communication, especially in intercultural contexts and presents tools & models to…

more ›### Exploiting Independence for Optimal Gaussian Importance Sampling

Stefan Heyder, TU Ilmenau 2.9.1.2210:00 - 11:00

Importance sampling is a Monte Carlo technique that estimates posterior expectations in Bayesian computation by sampling from a tractable proposal…

more ›### Self-organization of dynamic network structure of mesoderm cells

Mitsusuke Tarama, Kyushu University 2.28.1.00113:00 - 14:30

Self-organization of various cellular structures is of fundamental importance in morphogenesis during development of biological organisms. Our…

more ›### Random dynamical models & invariant uniform statistics: applications to particle filtering, model assessment and machine learning

Joaquín Miguez, Universidad Carlos III de Madrid 2.29.0.25/0.2613:00 - 14:00

We begin with a class of particle filters (PFs) that can automatically tune their performance by the online evaluation of certain predictive…

more ›### IRTG Networking Meeting

Joaquín Miguez & David Albers 2.29.0.25/0.2614:00 - 15:00

Our IRTG Networking Meeting with Joaquín Miguez and David Albers provides a chance to talk about career, chances, and the challenges in academia.

more ›### Inverse problems, systems physiology, and human health: an interdisciplinary survey of three foundational problems

David Albers, University of Colorado, USA 2.9.2.2210:15 - 11:30

We would like to use data collected from humans to forward our understanding of physiological mechanics and to improve human health. However, because…

more ›### Jamboree 2024 - IRTG and associated members

The Jamboree 2023 for all members of the IRTG as well as associated members will take place from march 13th to 15th at the Waldhotel Berghof. This…

more ›### A time-adaptive optimal control approach for 4D-var data assimilation problems governed by parabolic PDEs

Jannis Marquardt, TU Braunschweig 2.9.1.2215:00 - 17:30

Seminar talk followed by a young researcher network meeting.

Abstract:

The common solution techniques of the data assimilation problem typically…

more ›### Reconstruction of electron radiation belts using numerical modeling, data assimilation and machine learning

Alexander Drozdov, University of California, Los Angeles 2.9.1.2210:00 - 12:00

This seminar presented an overview of numerical modeling, data assimilation, and machine learning in understanding Earth's electron radiation belts.…

more ›### Design of OSE and OSSE for Earth’s radiation belts

Quintin Schiller, Space Science Institute 2.9.2.2210:30 - 12:00

Earth’s Van Allen radiation belts, located in near-Earth space, are comprised of very energetic electrons and protons. However, the origins of these…

more ›### IRTG Workshop: Scientific Writing (Part I)

Dr Martina Michalikova, Writing Scientist Griebnitzsee, House 7, R. 1.27 - 1.2909:00 - 17:00

Dr Martina Michalikova gives a two-day scientific writing workshop on the 6th and 7th of June 2024, from 9 a.m. - 5 p.m.

**Please bring the following…**

### Variational Inference for (Neural) SDEs Driven by Fractional Noise

Rembert Daems, Dynamics and Design Lab, Ghent University, Belgium 2.28.2.12310:30 - 12:00

Stochastic differential equations (SDEs) offer a versatile tool for modeling real-world continuous-time dynamic systems with inherent noise and…

more ›### Joint seminar with Kevin Burrage

Kevin Burrage, Queensland University of Technology, Australia 2.9.2.2210:15 - 11:45

Joint seminar with the RF Data-Centric-Sciences

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