33 citations · 157 across the 27 of their papers we have counts for
6 papers · 1 filter
Interpretable transformed ANOVA approximation on the example of the prevention of forest fires
Daniel Potts, Michael Schmischke
The distribution of data points is a key component in machine learning. In most cases, one uses min-max normalization to obtain nodes in or Z-score normalization for standa…
The uniform sparse FFT with application to PDEs with random coefficients
Lutz Kämmerer, Daniel Potts, Fabian Taubert
We develop the uniform sparse Fast Fourier Transform (usFFT), an efficient, non-intrusive, adaptive algorithm for the solution of elliptic partial differential equations with rando…
Fast Hyperbolic Wavelet Regression meets ANOVA
Laura Lippert, Daniel Potts, Tino Ullrich
We use hyperbolic wavelet regression for the fast reconstruction of high-dimensional functions having only low dimensional variable interactions. Compactly supported periodic Chui-…
Nonuniform fast Fourier transforms with nonequispaced spatial and frequency data and fast sinc transforms
Melanie Kircheis, Daniel Potts, Manfred Tasche
In this paper we study the nonuniform fast Fourier transform with nonequispaced spatial and frequency data (NNFFT) and the fast sinc transform as its application. The computation o…
Interpretable Approximation of High-Dimensional Data
Daniel Potts, Michael Schmischke
In this paper we apply the previously introduced approximation method based on the ANOVA (analysis of variance) decomposition and Grouped Transformations to synthetic and real data…
A note on transformed Fourier systems for the approximation of non-periodic signals
Robert Nasdala, Daniel Potts
A variety of techniques have been developed for the approximation of non-periodic functions. In particular, there are approximation techniques based on rank- lattices and transf…