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Journal Articles
- 2024
[j9]Chethan Krishnamurthy Ramanaik
, Anna Willmann, Juan Esteban Suarez Cardona, Pia Hanfeld, Nico Hoffmann, Michael Hecht:
Ensuring Topological Data-Structure Preservation under Autoencoder Compression Due to Latent Space Regularization in Gauss-Legendre Nodes. Axioms 13(8): 535 (2024)- [j8]Gentian Zavalani, Elima Shehu, Michael Hecht:
A note on the rate of convergence of integration schemes for closed surfaces. Comput. Appl. Math. 43(2): 92 (2024) - [j7]Juan Esteban Suarez Cardona, Phil-Alexander Hofmann, Michael Hecht:
Negative order sobolev cubatures: preconditioners of partial differential equation learning tasks circumventing numerical stiffness. Mach. Learn. Sci. Technol. 5(3): 35029 (2024) - 2023
- [j6]Damar Wicaksono, Michael Hecht:
UQTestFuns: A Python3 library of uncertainty quantification (UQ) test functions. J. Open Source Softw. 8(91): 5671 (2023) - [j5]Juan Esteban Suarez Cardona, Michael Hecht:
Polynomial differentiation decreases the training time complexity of physics-informed neural networks and strengthens their approximation power. Mach. Learn. Sci. Technol. 4(4): 45005 (2023) - [j4]Sachin K. Thekke Veettil, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, Michael Hecht:
Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces. SIAM J. Sci. Comput. 45(4): 1995- (2023) - 2021
- [j3]Michael Hecht, Krzysztof Gonciarz, Szabolcs Horvát:
Tight Localizations of Feedback Sets. ACM J. Exp. Algorithmics 26: 1.5:1-1.5:19 (2021) - 2018
- [j2]Michael Hecht:
Exact Localisations of Feedback Sets. Theory Comput. Syst. 62(5): 1048-1084 (2018) - 2017
- [j1]Michael Hecht:
A generalization of the most common subgraph distance and its application to graph editing. Pattern Recognit. Lett. 87: 71-78 (2017)
Conference and Workshop Papers
- 2023
- [c1]Janina Schreiber, Damar Wicaksono, Michael Hecht:
Minimizing Black Boxes due to Polynomial-Model-Based Optimization. GECCO Companion 2023: 759-762
Informal and Other Publications
- 2024
- [i14]Janina Schreiber, Pau Batlle, Damar Wicaksono, Michael Hecht:
PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates. CoRR abs/2403.07485 (2024) - [i13]Gentian Zavalani, Michael Hecht:
High-order numerical integration on regular embedded surfaces. CoRR abs/2403.09178 (2024) - [i12]Juan Esteban Suarez Cardona, Shashank Reddy, Michael Hecht:
Hybrid Surrogate Models: Circumventing Gibbs Phenomenon for Partial Differential Equations with Finite Shock-Type Discontinuities. CoRR abs/2408.02497 (2024) - 2023
- [i11]Juan Esteban Suarez Cardona, Phil-Alexander Hofmann, Michael Hecht:
Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces. CoRR abs/2301.04887 (2023) - [i10]Janina Schreiber, Damar Wicaksono, Michael Hecht:
Polynomial-Model-Based Optimization for Blackbox Objectives. CoRR abs/2309.00663 (2023) - [i9]Chethan Krishnamurthy Ramanaik, Juan Esteban Suarez Cardona, Anna Willmann, Pia Hanfeld, Nico Hoffmann, Michael Hecht:
Ensuring Topological Data-Structure Preservation under Autoencoder Compression due to Latent Space Regularization in Gauss-Legendre nodes. CoRR abs/2309.08228 (2023) - [i8]Gentian Zavalani, Oliver Sander, Michael Hecht:
High-Order Integration on regular triangulated manifolds reaches Super-Algebraic Approximation Rates through Cubical Re-parameterizations. CoRR abs/2311.13909 (2023) - 2022
- [i7]Juan Esteban Suarez Cardona, Michael Hecht:
Replacing Automatic Differentiation by Sobolev Cubatures fastens Physics Informed Neural Nets and strengthens their Approximation Power. CoRR abs/2211.15443 (2022) - [i6]Sachin K. Thekke Veettil, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, Michael Hecht:
Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces. CoRR abs/2212.11536 (2022) - [i5]Sachin K. Thekke Veettil, Yuxi Zheng, Uwe Hernandez Acosta, Damar Wicaksono, Michael Hecht:
Multivariate Polynomial Regression of Euclidean Degree Extends the Stability for Fast Approximations of Trefethen Functions. CoRR abs/2212.11706 (2022) - 2021
- [i4]Nishant Kumar, Pia Hanfeld, Michael Hecht, Michael Bussmann, Stefan Gumhold, Nico Hoffmann:
InFlow: Robust outlier detection utilizing Normalizing Flows. CoRR abs/2106.12894 (2021) - 2020
- [i3]Michael Hecht, Krzysztof Gonciarz, Szabolcs Horvát:
Tight Localizations of Feedback Sets. CoRR abs/2001.01440 (2020) - [i2]Michael Hecht, Krzysztof Gonciarz, Jannik Michelfeit, Vladimir Sivkin, Ivo F. Sbalzarini:
Multivariate Interpolation on Unisolvent Nodes - Lifting the Curse of Dimensionality. CoRR abs/2010.10824 (2020) - 2017
- [i1]Michael Hecht:
Exact Localisations of Feedback Sets. CoRR abs/1702.07612 (2017)
Coauthor Index
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