Colloquia in 2023
Deep Learning Statistical Tests for Genetic Studies of Image Phenotypes
Christoph Lippert, HPI - Digital Health - Machine Learning Campus Golm, Building 28, Room 0.10810:15 - 11:15
In my talk I will give an overview on our ongoing work on the development of methods for finding associations between variation that is encoded in…
more ›Understanding and Applying Reinforcement Learning
Claire Vernade, DeepMind Campus Golm, Building 28, Room 0.10810:15 - 11:30
Reinforcement Learning (RL) builds learning systems from the ground up by trial and error: as the agent takes actions, they receive rewards and…
more ›Seasonal forecasting - opportunities and challenges
Antje Weisheimer, European Centre for Medium-Range Weather Forecasts 2.28.0.10810:15 - 11:30
Seasonal forecasts aim to provide physically-based probabilistic outlooks of the climate conditions for the coming seasons. We create them by…
more ›Conservative SPDEs as fluctuating mean field limits of stochastic gradient descent
Vitalii Konarovskyi, University of Bielefeld 2.28.0.10810:15 - 11:30
My talk will be devoted to the convergence of stochastic interacting particle systems in the mean-field limit to solutions of conservative SPDEs. We…
more ›On the design of scientific visualization
Nicolas Rougier, INRIA, Bordeaux 2.9.2.2214:00 - 15:30
This is a co-organized colloquium with the Institute of Mathematics of the UP
Scientific visualization is classically defined as the process of…
more ›Research data in mathematics, FAIRness, and the MaRDI consortium
Tabea Krause & Tabea Bacher, MaRDI 2.28.0.10810:15 - 11:30
In this talk we will introduce a definition of 'research data' in mathematics which encompasses all digital objects you handle in the process of doing…
more ›Model Order Reduction in Data Assimilation
Karen Veroy-Grepl, Eindhoven University of Technology 2.28.0.10810:15 - 11:30
The use of model order reduction techniques in combination with data assimilation methods for estimating the state of systems has been of great…
more ›6th Kálmán Lecture with Richard Nickl
Richard Nickl, University of Cambridge 3.06.H0209:30 - 10:30
This year, Kalman Lecture will be held by Richard Nickl from University of Cambridge. His talk on 'On posterior consistency in non-linear Bayesian…
more ›On polynomial-time mixing for high-dimensional MCMC in inverse problems
Sven Wang, HU Berlin 2.28.0.10810:15-11:15
We consider the problem of generating random samples from high-dimensional posterior distributions. We will discuss both (i) conditions under which…
more ›Discretization-adaptive regularization of inverse problems
Tim Jahn2.28.0.10810:15-11:15
We consider linear inverse problems under white (non-Gaussian) noise. For the solution we have to discretize the problem, and we consider a sequence…
more ›Uncertainty Quantification and Attribution in Models of the Earth System
Thorsten Wagener, University of Potsdam 2.28.0.10810:15-11:15
The recent State of Global Water Resources report by the World Meteorological Organization concluded that the hydrological cycle is spinning out of…
more ›