Events in 2021

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

Unfortunately we had to cancel this Colloquium.

invited by Yuri Shprits

***Due to the current pandemic this colloquium will be conducted online.…

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

Like in all scientific disciplines research data in mathematics has become vast, it is complex and multifaceted, and, through the successful…

The class of integer-valued trawl processes has recently been introduced for modelling univariate and multivariate integer-valued time series with…

Almost 200 years ago, Alexander von Humboldt said in his famous Cosmos series that „all natural forces are linked together, and made mutually…

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

Cellular signal transduction system is a complex reaction network consisting of many elements, which  allows cells to respond appropriately to…

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

We are kicking of the 2nd Phase of our SFB with a 1,5 day Kick-Off Event on the 14th and 15th of September!

This includes our annual meeting, poster…

The initial state for a geophysical numerical model is produced by combining observational data with numerical model simulation using a data…

Many practical Bayesian inference problems fall into the "likelihood-free" setting, where evaluations of the likelihood function or prior density are…

The goal of actor critic methods is to estimate the best policy among a parameterized family for a controlled Markov chain.   Through the magic of…

tba

invited by Carsten Beta

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…

Quantitative epistemology: conceiving a new human-machine partnership

Quantitative epistemology is a new and transformational area of research…

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

Complex dynamical systems like molecular systems or stochastic climate systems often involve a variety of different time and length scales. We propose…

We propose a systematic | theoretical | statistical analysis for systems of interacting
diffusions, possibly with common noise and/or degenerate…

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

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

The use of AI has improved computer-aided diagnosis systems in many areas. However, the underlying models are often black boxes that allow the user…

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 in high dimensions has been a most active research topics in the last
decade. Both theoretical and practical considerations make it…

Our long term student assistant, Anja Seegebrecht, from project Z03 will give an overview over the topic of her master thesis, which was conducted at…

Neutron stars are among the most compact objects in the Universe and the detection of gravitational waves and electromagnetic signals from the merger…