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Publikationen

Potts, D., & Schmischke, M. (2022). Learning multivariate functions with low-dimensional structures using polynomial bases. Journal of Computational and Applied Mathematics, 403, 113821. https://doi.org/10.1016/j.cam.2021.113821
Potts, D., & Schmischke, M. (2022). Interpretable Transformed ANOVA Approximation on the Example of the Prevention of Forest Fires. Frontiers in Applied Mathematics and Statistics, 8, 795250. https://doi.org/10.3389/fams.2022.795250
Potts, D., & Schmischke, M. (2021). Interpretable Approximation of High-Dimensional Data. SIAM Journal on Mathematics of Data Science, 3(4), 1301-1323. https://doi.org/10.1137/21M1407707
Potts, D., & Schmischke, M. (2021). Approximation of high-dimensional periodic functions with Fourier-based methods. SIAM Journal on Numerical Analysis, 59, 9. https://doi.org/10.1137/20M1354921
Potts, D., & Tasche, M. (2021). Continuous window functions for NFFT. Advances in Computational Mathematics, 47, 53. https://doi.org/10.1007/s10444-021-09873-8
Potts, D., & Tasche, M. (2021). Uniform error estimates for nonequispaced fast Fourier transforms. Sampling Theory, Signal Processing, and Data Analysis, 19, 17. https://doi.org/10.1007/s43670-021-00017-z