Daniel Potts | DeepAI

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Martin Stoll
29 publications
Tino Ullrich
20 publications
Lutz Kämmerer
8 publications
Toni Volkmer
7 publications
Felix Bartel
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Michael Schmischke
6 publications
Manfred Tasche
5 publications
Melanie Kircheis
5 publications
Dominik Alfke
4 publications
Laura Lippert
3 publications
Fabian Taubert
3 publications

∙ 06/30/2023

On numerical realizations of Shannon's sampling theorem

In this paper, we discuss some numerical realizations of Shannon's sampl...

0 Melanie Kircheis, et al. ∙

∙ 06/15/2023

ANOVA approximation with mixed tensor product basis on scattered points

In this paper we consider an orthonormal basis, generated by a tensor pr...

0 Daniel Potts, et al. ∙

∙ 03/31/2023

Optimal density compensation factors for the reconstruction of the Fourier transform of bandlimited functions

An inverse nonequispaced fast Fourier transform (iNFFT) is a fast algori...

0 Melanie Kircheis, et al. ∙

∙ 02/01/2023

Fast and direct inversion methods for the multivariate nonequispaced fast Fourier transform

The well-known discrete Fourier transform (DFT) can easily be generalize...

0 Melanie Kircheis, et al. ∙

∙ 11/11/2022

Nonlinear approximation in bounded orthonormal product bases

We present a dimension-incremental algorithm for the nonlinear approxima...

0 Lutz Kämmerer, et al. ∙

∙ 08/29/2022

On the reconstruction of functions from values at subsampled quadrature points

This paper is concerned with function reconstruction from samples. The s...

0 Felix Bartel, et al. ∙

∙ 07/26/2022

Variable Transformations in combination with Wavelets and ANOVA for high-dimensional approximation

We use hyperbolic wavelet regression for the fast reconstruction of high...

0 Laura Lippert, et al. ∙

∙ 03/18/2022

On regularized Shannon sampling formulas with localized sampling

In this paper we present new regularized Shannon sampling formulas which...

0 Melanie Kircheis, et al. ∙

∙ 10/14/2021

Interpretable transformed ANOVA approximation on the example of the prevention of forest fires

The distribution of data points is a key component in machine learning. ...

5 Daniel Potts, et al. ∙

∙ 09/09/2021

The uniform sparse FFT with application to PDEs with random coefficients

We develop an efficient, non-intrusive, adaptive algorithm for the solut...

0 Lutz Kämmerer, et al. ∙

∙ 08/30/2021

Fast Hyperbolic Wavelet Regression meets ANOVA

We use hyperbolic wavelet regression for the fast reconstruction of high...

0 Laura Lippert, et al. ∙

∙ 07/06/2021

Nonuniform fast Fourier transforms with nonequispaced spatial and frequency data and fast sinc transforms

In this paper we study the nonuniform fast Fourier transform with nonequ...

0 Melanie Kircheis, et al. ∙

∙ 03/25/2021

Interpretable Approximation of High-Dimensional Data

In this paper we apply the previously introduced approximation method ba...

8 Daniel Potts, et al. ∙

∙ 02/01/2021

A note on transformed Fourier systems for the approximation of non-periodic signals

A variety of techniques have been developed for the approximation of non...

0 Robert Nasdala, et al. ∙

∙ 10/20/2020

Grouped Transformations in High-Dimensional Explainable ANOVA Approximation

Many applications are based on the use of efficient Fourier algorithms s...

0 Felix Bartel, et al. ∙

∙ 10/14/2020

Continuous window functions for NFFT

In this paper, we study the error behavior of the nonequispaced fast Fou...

0 Daniel Potts, et al. ∙

∙ 12/20/2019

Uniform error estimates for the NFFT

In this paper, we study the error behavior of the known fast Fourier tra...

0 Daniel Potts, et al. ∙

∙ 12/06/2019

Learning multivariate functions with low-dimensional structures using polynomial bases

In this paper we study the multivariate ANOVA decomposition for function...

0 Daniel Potts, et al. ∙

∙ 12/06/2019

Efficient multivariate approximation on the cube

For the approximation of multivariate non-periodic functions h on the hi...

0 Robert Nasdala, et al. ∙

∙ 07/26/2019

Learning high-dimensional additive models on the torus

In this paper we study the multivariate ANOVA decomposition for 1-period...

0 Daniel Potts, et al. ∙

∙ 08/14/2018

NFFT meets Krylov methods: Fast matrix-vector products for the graph Laplacian of fully connected networks

The graph Laplacian is a standard tool in data science, machine learning...

6 Dominik Alfke, et al. ∙

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