2 citations · 2 across the 3 of their papers we have counts for
8 papers
Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue
Shahnewaz Shuva, Patrick Buchfink, Oliver Röhrle +1
We present efficient reduced basis (RB) methods for the simulation of the coupled problem consisting of a rigid robot hand interacting with soft tissue material which is modeled by…
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem
Bernard Haasdonk, Boumediene Hamzi, Gabriele Santin +1
For dynamical systems with a non hyperbolic equilibrium, it is possible to significantly simplify the study of stability by means of the center manifold theory. This theory allows…
Deep recurrent Gaussian process with variational Sparse Spectrum approximation
Roman Föll, Bernard Haasdonk, Markus Hanselmann +1
Modeling sequential data has become more and more important in practice. Some applications are autonomous driving, virtual sensors and weather forecasting. To model such systems, s…
Enabling Interactive Mobile Simulations Through Distributed Reduced Models
Christoph Dibak, Bernard Haasdonk, Andreas Schmidt +2
Currently, various hardware and software companies are developing augmented reality devices, most prominently Microsoft with its Hololens. Besides gaming, such devices can be used…
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario
Markus Köppel, Fabian Franzelin, Ilja Kröker +8
A variety of methods is available to quantify uncertainties arising with\-in the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough compariso…
Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods
Tobias Köppl, Gabriele Santin, Bernard Haasdonk +1
In this work, we consider two kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery i…