24 citations · 45 across the 12 of their papers we have counts for
12 papers
Noise calibration for the stochastic rotating shallow water model
Dan Crisan, Oana Lang, Alexander Lobbe +2
Stochastic partial differential equations have been used in a variety of contexts to model the evolution of uncertain dynamical systems. In recent years, their applications to geop…
Inverse medium scattering problems with Kalman filter techniques
Takashi Furuya, Roland Potthast
We study the inverse medium scattering problem to reconstruct the unknown inhomogeneous medium from the far-field patterns of scattered waves. The inverse scattering problem is gen…
Particle Filtering and Gaussian Mixtures -- On a Localized Mixture Coefficients Particle Filter (LMCPF) for global NWP
Anne Rojahn, Nora Schenk, Peter Jan van Leeuwen +1
In a global numerical weather prediction (NWP) modeling framework we study the implementation of Gaussian uncertainty of individual particles into the assimilation step of a locali…
Bayesian Inference for Fluid Dynamics: A Case Study for the Stochastic Rotating Shallow Water Model
Peter Jan van Leeuwen, Dan Crisan, Oana Lang +1
In this work, we use a tempering-based adaptive particle filter to infer from a partially observed stochastic rotating shallow water (SRSW) model which has been derived using the S…
Inverse medium scattering problems with Kalman filter techniques II. Nonlinear case
Takashi Furuya, Roland Potthast
In this paper, we study the inverse medium scattering problem to reconstruct unknown inhomogeneous medium from far field patterns of scattered waves. In the first part of our work,…
Inverse medium scattering problems with Kalman filter techniques I. Linear case
Takashi Furuya, Roland Potthast
In this paper, we study the inverse acoustic medium scattering problem to reconstruct the unknown inhomogeneous medium from far field patterns of scattered waves. We propose the re…
Regularising linear inverse problems under unknown non-Gaussian white noise allowing repeated measurements
Bastian Harrach, Tim Jahn, Roland Potthast
We deal with the solution of a generic linear inverse problem in the Hilbert space setting. The exact right hand side is unknown and only accessible through discretised measurement…
Duality between range and no-response tests and its application for inverse problems
Yi-Hsuan Lin, Gen Nakamura, Roland Potthast +1
In this paper we will show the duality between the range test (RT) and no-response test (NRT) for the inverse boundary value problem for the Laplace equation in $Ω\setminus\overlin…
Beyond the Bakushinskii veto: Regularising linear inverse problems without knowing the noise distribution
Bastian Harrach, Tim Jahn, Roland Potthast
This article deals with the solution of linear ill-posed equations in Hilbert spaces. Often, one only has a corrupted measurement of the right hand side at hand and the Bakushinski…
Particle filters for high-dimensional geoscience applications: a review
Peter Jan van Leeuwen, Hans R. Künsch, Lars Nerger +2
Particle filters contain the promise of fully nonlinear data assimilation. They have been applied in numerous science areas, but their application to the geosciences has been limit…
Universal neural field computation
Peter beim Graben, Roland Potthast
Turing machines and Gödel numbers are important pillars of the theory of computation. Thus, any computational architecture needs to show how it could relate to Turing machines and…
Implementing Turing Machines in Dynamic Field Architectures
Peter beim Graben, Roland Potthast
Cognitive computation such as e.g. language processing, is conventionally regarded as Turing computation, and Turing machines can be uniquely implemented as nonlinear dynamical sys…