92 citations · 108 across the 4 of their papers we have counts for
7 papers
Model order reduction of layered waveguides via rational Krylov fitting
Vladimir Druskin, Stefan Güttel, Leonid Knizhnerman
Rational approximation recently emerged as an efficient numerical tool for the solution of exterior wave propagation problems. Currently, this technique is limited to wave media wh…
An efficient aggregation method for the symbolic representation of temporal data
Xinye Chen, Stefan Güttel
Symbolic representations are a useful tool for the dimension reduction of temporal data, allowing for the efficient storage of and information retrieval from time series. They can…
A comparison of limited-memory Krylov methods for Stieltjes functions of Hermitian matrices
Stefan Güttel, Marcel Schweitzer
Given a limited amount of memory and a target accuracy, we propose and compare several polynomial Krylov methods for the approximation of f(A)b, the action of a Stieltjes matrix fu…
ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series
Steven Elsworth, Stefan Güttel
A new symbolic representation of time series, called ABBA, is introduced. It is based on an adaptive polygonal chain approximation of the time series into a sequence of tuples, fol…
Time Series Forecasting Using LSTM Networks: A Symbolic Approach
Steven Elsworth, Stefan Güttel
Machine learning methods trained on raw numerical time series data exhibit fundamental limitations such as a high sensitivity to the hyper parameters and even to the initialization…
Algorithms for the rational approximation of matrix-valued functions
Ion Victor Gosea, Stefan Güttel
A selection of algorithms for the rational approximation of matrix-valued functions are discussed, including variants of the interpolatory AAA method, the RKFIT method based on app…
Limited-memory polynomial methods for large-scale matrix functions
Stefan Güttel, Daniel Kressner, Kathryn Lund
Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various li…