Upcoming Events

Many events are currently organized online. Information on how to access these events can be found by clicking “more” below the respective entry.


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June 29 – July 1, 2022 (Harnack-Haus)
Workshop/Konferenz: Random Point Processes in Statistical Physics
more ... Location
Harnack-Haus -- Tagungsstätte der Max-Planck-Gesellschaft

Host
WIAS Berlin
DFG Schwerpunktprogramm 2265
July 5 – 8, 2022 (WIAS-ESH)
Workshop/Konferenz: Workshop on Numerical Methods and Analysis in CFD
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Host
WIAS Berlin
Tuesday, 05.07.2022, 15:00 (WIAS-405-406)
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Alexander Marx, WIAS Berlin:
Random interactions in the mean-field Ising model (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Further Informations
Dieser Vortrag findet bei Zoom statt: https://zoom.us/j/492088715

Host
WIAS Berlin
Wednesday, 06.07.2022, 10:00 (WIAS-405-406)
Forschungsseminar Mathematische Statistik
Prof. Vincent Rivoirard, Université Paris Dauphine, Frankreich:
Nonparametric Bayesian estimation of nonlinear Hawkes process (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Abstract
Multivariate point processes are widely applied to model event-type data such as natural disasters, online message exchanges, financial transactions or neuronal spike trains. One very popular point process model in which the probability of occurrences of new events depend on the past of the process is the Hawkes process. In this work we consider the nonlinear Hawkes process, which notably models excitation and inhibition phenomena between dimensions of the process. In a nonparametric Bayesian estimation framework, we obtain concentration rates of the posterior distribution on the parameters, under mild assumptions on the prior distribution and the model. These results also lead to convergence rates of Bayesian estimators. Another object of interest in event-data modelling is to recover the graph of interaction of the phenomenon. We provide consistency guarantees on Bayesian methods for estimating this quantity; in particular, we prove that the posterior distribution is consistent on the graph adjacency matrix of the process, as well as a Bayesian estimator based on an adequate loss function. Joint work with Judith Rousseau and Deborah Sulem.

Further Informations
Der Vortrag findet bei Zoom statt: https://zoom.us/j/159082384

Host
Humboldt-Universität zu Berlin
WIAS Berlin
Universität Potsdam
July 13 – 15, 2022 (WIAS-ESH)
Workshop/Konferenz: Nonlinear Waves and Turbulence in Photonics 2022
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
The workshop "Nonlinear Waves and Turbulence in Photonics" (NWTP22) will bring together leading experts in the field of nonlinear optics and photonics. The workshop's guiding idea is to provide an international platform which leads to a more comprehensive understanding of fundamental nonlinear phenomena, such as wave-turbulence, solitons, and extreme waves. We expect exciting reports and fruitful discussions both on the most recent advances in the field and promising future developments.

Host
WIAS Berlin
Wednesday, 13.07.2022, 10:00 (WIAS-405-406)
Seminar Interacting Random Systems
Quirin Vogel, NYU Shanghai, China, Volksrepublik:
tba
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Further Informations
Seminar Interacting Random Systems

Host
WIAS Berlin
Wednesday, 20.07.2022, 15:15 (WIAS-ESH)
Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Dr. Nikita Simonov, LaMMe-Universitè d'Évry Val d'Essone, France:
Fast diffusion equations, tails and convergence rates
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
Understanding the intermediate asymptotic and computing convergence rates towards equilibria are among the major problems in the study of parabolic equations. Convergence rates depend on the tail behaviour of solutions. This observation raised the following question: how can we understand the tail behaviour of solutions from the tail behaviour of the initial datum? In this talk, I will discuss the asymptotic behaviour of solutions to the fast diffusion equation. It is well known that non-negative solutions behave for large times as the Barenblatt (or fundamental) solution, which has an explicit expression. In this setting, I will introduce the Global Harnack Principle (GHP), precise global pointwise upper and lower estimates of non-negative solutions in terms of the Barenblatt profile. I will characterize the maximal (hence optimal) class of initial data such that the GHP holds by means of an integral tail condition. As a consequence, I will provide rates of convergence towards the Barenblatt profile in entropy and in stronger norms such as the uniform relative error.

Host
Humboldt-Universität zu Berlin
WIAS Berlin