| Multivariate Interpolation on Unisolvent Nodes--Lifting the Curse of Dimensionality M Hecht, K Gonciarz, J Michelfeit, V Sivkin, IF Sbalzarini arXiv preprint arXiv:2010.10824, 2020 | 16 | 2020 |
| Multivariate Newton interpolation M Hecht, KB Hoffmann, BL Cheeseman, IF Sbalzarini arXiv preprint arXiv:1812.04256, 2018 | 16 | 2018 |
| Fast interpolation and Fourier transform in high-dimensional spaces M Hecht, IF Sbalzarini Science and Information Conference, 53-75, 2018 | 16 | 2018 |
| A quadratic-time algorithm for general multivariate polynomial interpolation M Hecht, BL Cheeseman, KB Hoffmann, IF Sbalzarini arXiv preprint arXiv:1710.10846, 2017 | 14 | 2017 |
| Exact localisations of feedback sets M Hecht Theory of Computing Systems 62, 1048-1084, 2018 | 13 | 2018 |
| Extraction of the frequency moments of spectral densities from imaginary-time correlation function data T Dornheim, DC Wicaksono, JE Suarez-Cardona, P Tolias, MP Böhme, ... Physical Review B 107 (15), 155148, 2023 | 9 | 2023 |
| Multivariate polynomial regression of Euclidean degree extends the stability for fast approximations of Trefethen functions SKT Veettil, Y Zheng, UH Acosta, D Wicaksono, M Hecht arXiv preprint arXiv:2212.11706, 2022 | 7 | 2022 |
| InFlow: Robust outlier detection utilizing normalizing flows N Kumar, P Hanfeld, M Hecht, M Bussmann, S Gumhold, N Hoffmann arXiv preprint arXiv:2106.12894, 2021 | 7 | 2021 |
| Tight localizations of feedback sets M Hecht, K Gonciarz, S Horvát Journal of Experimental Algorithmics (JEA) 26, 1-19, 2021 | 6 | 2021 |
| Replacing automatic differentiation by sobolev cubatures fastens physics informed neural nets and strengthens their approximation power JES Cardona, M Hecht arXiv preprint arXiv:2211.15443, 2022 | 4 | 2022 |
| A generalization of the most common subgraph distance and its application to graph editing M Hecht Pattern Recognition Letters 87, 71-78, 2017 | 4 | 2017 |
| Isomorphic chain complexes of Hamiltonian dynamics on tori M Hecht Journal of Fixed Point Theory and Applications 14, 165-221, 2013 | 4 | 2013 |
| A note on the rate of convergence of integration schemes for closed surfaces G Zavalani, E Shehu, M Hecht Computational and Applied Mathematics 43 (2), 1-17, 2024 | 1 | 2024 |
| High-Order Integration on regular triangulated manifolds reaches Super-Algebraic Approximation Rates through Cubical Re-parameterizations G Zavalani, O Sander, M Hecht arXiv preprint arXiv:2311.13909, 2023 | 1 | 2023 |
| UQTestFuns: A Python3 library of uncertainty quantification (UQ) test functions D Wicaksono, M Hecht Journal of Open Source Software 8 (90), 5671, 2023 | 1 | 2023 |
| Global polynomial level sets for numerical differential geometry of smooth closed surfaces SKT Veettil, G Zavalani, UH Acosta, IF Sbalzarini, M Hecht SIAM Journal on Scientific Computing 45 (4), A1995-A2018, 2023 | 1 | 2023 |
| Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces JES Cardona, PA Hofmann, M Hecht arXiv preprint arXiv:2301.04887, 2023 | 1 | 2023 |
| High-order numerical integration on regular embedded surfaces G Zavalani, M Hecht arXiv preprint arXiv:2403.09178, 2024 | | 2024 |
| PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates J Schreiber, P Batlle, D Wicaksono, M Hecht arXiv preprint arXiv:2403.07485, 2024 | | 2024 |
| Polynomial differentiation decreases the training time complexity of physics-informed neural networks and strengthens their approximation power JES Cardona, M Hecht Machine Learning: Science and Technology 4 (4), 045005, 2023 | | 2023 |
