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Monday, 23.04.2018, 14:00 (WIAS-ESH)
Seminar Quantitative Biomedizin
Prof. S. Waters, University of Oxford, GB:
Fluid dynamical models for tissue engineering
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
Tissue engineers aim to grow tissues in vitro to replace those in the body that have been damaged through age, trauma or disease. A common approach is to seed cells within a scaffold which is then cultured in a bioreactor. The key challenge it to provide the appropriate mechanical and biochemical cellular environment that promotes tissue growth in vitro. Fluid flows have a key role to play in addressing this challenge, as they can provide mechanical cues to cells (e.g. via fluid shear and pressure), and enhance the delivery of nutrients and growth factors (via advection). In this talk, I will explore how mechanistic mathematical models, in combination with state-of-the art experimental studies, can provide quantitative insights into the interplay between the fluid flows and the resulting tissue growth. Quantitative understanding of this interplay offers the exciting potential to manipulate the experimental design (e.g. scaffold porosity, bioreactor operating conditions) to establish defined mechanical cues that enhance the generation of complex 3D tissues in vitro.

Host
WIAS Berlin
Wednesday, 25.04.2018, 10:00 (WIAS-ESH)
Forschungsseminar Mathematische Statistik
N. Baldin, University of Cambridge, GB:
Optimal link prediction with matrix logistic regression
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
In this talk, we will consider the problem of link prediction, based on partial observation of a large network, and on side information associated to its vertices. The generative model is formulated as a matrix logistic regression. The performance of the model is analysed in a high-dimensional regime under a structural assumption. The minimax rate for the Frobenius-norm risk is established and a combinatorial estimator based on the penalised maximum likelihood approach is shown to achieve it. Furthermore, it is shown that this rate cannot be attained by any (randomised) algorithm computable in polynomial time under a computational complexity assumption. (joint work with Q. Berthet)

Further Informations
Forschungsseminar “Mathematische Statistik”

Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
Thursday, 03.05.2018, 14:00 (WIAS-ESH)
Seminar Numerische Mathematik
Dr. H. Stephan, WIAS Berlin:
One million perrin pseudo primes including a few giants
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
Pseudoprimes are integers that are no primes but behave like them in some sense. Suppose we have a theorem like the following: If n is a prime, then statement A(n) holds. In general, the opposite is not true: It may be that A(n) holds, but n is a composite number, a so-called pseudo prime with respect to statement A. Pseudoprimes are interesting if they are very rare, as for instance Perrin's pseudoprimes, the smallest of which is 271441. The talk introduces pseudoprimes which are based on recurrent sequences. In addition, some new numerical results on Perrin's pseudoprimes and a fast algorithm for their calculation are presented.

Host
WIAS Berlin
Wednesday, 09.05.2018, 15:15 (WIAS-ESH)
Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Prof. A. Jüngel, Technische Universität Wien, Österreich:
Cross-diffusion systems with entropy structure
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
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Further Informations
Berliner Oberseminar “Nichtlineare Partielle Differentialgleichungen” (Langenbach Seminar)

Host
WIAS Berlin
Humboldt-Universität zu Berlin
Thursday, 17.05.2018, 10:15 (WIAS-406)
Seminar Nichtlineare Optimierung und Inverse Probleme
C. Geiersbach, Universität Wien, Österreich:
A projected stochastic gradient algorithm for optimization with random elliptic PDE constraints
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)

Host
WIAS Berlin
Wednesday, 23.05.2018, 15:15 (WIAS-ESH)
Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Prof. Dr. P. Colli, Università di Pavia, Italien:
A Cahn--Hilliard system with convection and dynamic boundary conditions: Well-posedness and optimal velocity control
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Further Informations
Berliner Oberseminar “Nichtlineare Partielle Differentialgleichungen” (Langenbach Seminar)

Host
WIAS Berlin
Humboldt-Universität zu Berlin
Wednesday, 30.05.2018, 10:00 (WIAS-ESH)
Forschungsseminar Mathematische Statistik
F. Schäfer, California Institute of Technology, USA:
Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
Many popular methods in machine learning, statistics, and uncertainty quantification rely on priors given by smooth Gaussian processes, like those obtained from the Mat Ì?ern covariance functions. Furthermore, many physical systems are described in terms of elliptic partial differential equa- tions. Therefore, implicitely or explicitely, numerical simulation of these systems requires an efficient numerical representation of the correspond- ing Greenâ??s operator. The resulting kernel matrices are typically dense, leading to (often prohibitive) O N2 or O N3 computational complexity. In this work, we prove rigorously that the dense N Ã? N kernel matri- ces obtained from elliptic boundary value problems and measurement points distributed approximately uniformly in a d-dimensional domain can be Cholesky factorised to accuracy ε in computational complexity O N log2(N)log2d(N/ε) in time and O N log(N)logd(N/ε) in space. For the closely related Mat Ì?ern covariances we observe very good results in practise, even for parameters corresponding to non-integer order equa- tions. As a byproduct, we obtain a sparse PCA with near-optimal low- rank approximation property and a fast solver for elliptic PDE. We emphasise that our algorithm requires no analytic expression for the covariance function. Our work is inspired by the probabilistic interpretation of the Cholesky factorisation, the screening effect in spatial statistics, and recent results in numerical homogenisation.

Further Informations
Forschungsseminar “Mathematische Statistik”

Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin