293 citations
- Freie Universität BerlinDE24 papers
- Technische Universität BerlinDE8 papers
- Humboldt-Universität zu BerlinDE5 papers
- Tel Aviv UniversityIL5 papers
- Exact Sciences (United States)US3 papers
- University of Illinois ChicagoUS3 papers
- ETH ZurichCH2 papers
- Institut des Hautes Études ScientifiquesFR2 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR2 papers
- Max Planck Institute for Gravitational PhysicsDE2 papers
- Universidade de São PauloBR2 papers
- Universität HamburgDE2 papers
6 papers · 1 filter
Subsampling in ensemble Kalman inversion
Matei Hanu, Jonas Latz, Claudia Schillings
We consider the Ensemble Kalman Inversion which has been recently introduced as an efficient, gradient-free optimisation method to estimate unknown parameters in an inverse setting…
Rigid continuation paths II. Structured polynomial systems
Peter Bürgisser, Felipe Cucker, Pierre Lairez
This work studies the average complexity of solving structured polynomial systems that are characterized by a low evaluation cost, as opposed to the dense random model previously u…
On energy conservation by trigonometric integrators in the linear case with application to wave equations
Ludwig Gauckler
Trigonometric integrators for oscillatory linear Hamiltonian differential equations are considered. Under a condition of Hairer & Lubich on the filter functions in the method, a mo…
Model Reduction for a Pulsed Detonation Combuster via Shifted Proper Orthogonal Decomposition
Philipp Schulze, Julius Reiss, Volker Mehrmann
We propose a new algorithm to compute a shifted proper orthogonal decomposition (sPOD) for systems dominated by multiple transport velocities. The sPOD is a recently proposed mode…
Adaptive Multilevel Monte Carlo Methods for Stochastic Variational Inequalities
Ralf Kornhuber, Evgenia Youett
While multilevel Monte Carlo (MLMC) methods for the numerical approximation of partial differential equations with random coefficients enjoy great popularity, combinations with spa…
Best subspace tensor approximations
S. Friedland, V. Mehrmann
In many applications such as data compression, imaging or genomic data analysis, it is important to approximate a given tensor by a tensor that is sparsely representable. For matri…