guest ::
| 001 | 981225 | ||
| 005 | 20260127075552.0 | ||
| 024 | 7 | _ | |2 DOI |a 10.48550/arXiv.2402.01402 |
| 024 | 7 | _ | |2 arXiv |a arXiv:2402.01402 |
| 024 | 7 | _ | |2 datacite_doi |a 10.18154/RWTH-2024-02871 |
| 037 | _ | _ | |a RWTH-2024-02871 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |0 P:(DE-82)IDM06352 |a Oster, Mathias |b 0 |u rwth |
| 245 | _ | _ | |a A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control |h online |
| 260 | _ | _ | |c 2024 |
| 300 | _ | _ | |a 29 Seiten |
| 336 | 7 | _ | |0 28 |2 EndNote |a Electronic Article |
| 336 | 7 | _ | |0 PUB:(DE-HGF)25 |2 PUB:(DE-HGF) |a Preprint |b preprint |m preprint |
| 336 | 7 | _ | |2 BibTeX |a ARTICLE |
| 336 | 7 | _ | |2 DRIVER |a preprint |
| 336 | 7 | _ | |2 DataCite |a Output Types/Working Paper |
| 336 | 7 | _ | |2 ORCID |a WORKING_PAPER |
| 588 | _ | _ | |a Dataset connected to arXivarXiv |
| 591 | _ | _ | |a Germany |
| 591 | _ | _ | |a Italy |
| 653 | _ | 7 | |a High-Dimensionality |
| 653 | _ | 7 | |a Kernel Methods |
| 653 | _ | 7 | |a Neural Networks |
| 653 | _ | 7 | |a Optimal Control |
| 653 | _ | 7 | |a Tensor Trains |
| 700 | 1 | _ | |a Saluzzi, Luca |b 1 |e Corresponding author |
| 700 | 1 | _ | |a Wenzel, Tizian |b 2 |
| 856 | 4 | _ | |u https://publications.rwth-aachen.de/record/981225/files/981225.pdf |y OpenAccess |
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| 910 | 1 | _ | |0 I:(DE-588b)36225-6 |6 P:(DE-82)IDM06352 |a RWTH Aachen |b 0 |k RWTH |
| 914 | 1 | _ | |y 2024 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0510 |2 StatID |a OpenAccess |
| 915 | _ | _ | |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |a Creative Commons Attribution CC BY 4.0 |
| 920 | 1 | _ | |0 I:(DE-82)111410_20170801 |k 111410 |l Lehrstuhl für Angewandte Mathematik und Institut für Geometrie und Praktische Mathematik |x 0 |
| 920 | 1 | _ | |0 I:(DE-82)110000_20140620 |k 110000 |l Fachgruppe Mathematik |x 1 |
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| 980 | _ | _ | |a I:(DE-82)111410_20170801 |
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| 980 | _ | _ | |a preprint |
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