Seminars in 2018
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 ›