Michael Hecht

31 papers Journal 30Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
PyLIT: Reformulation and implementation of the analytic continuation problem using kernel representation methods.
Comput. Phys. Commun.
Alexander Benedix Robles, Phil-Alexander Hofmann, Thomas Chuna, Tobias Dornheim, Michael Hecht
2025 J jnl
Automated detection of potential artifacts in machine learning based bio-image segmentation.
Mach. Learn. Sci. Technol.
Saiyam B. Jain, Zongru Shao, Michael Hecht
2025 J jnl
Fast Newton Transform: Interpolation in Downward Closed Polynomial Spaces.
CoRR
Phil-Alexander Hofmann, Damar Wicaksono, Michael Hecht
2025 J jnl
High-Order Integration on Regular Triangulated Manifolds Reaches Superalgebraic Approximation Rates Through Cubical Reparametrizations.
SIAM J. Numer. Anal.
Gentian Zavalani, Oliver Sander, Michael Hecht
2025 J jnl
Interpolation in Polynomial Spaces of p-Degree.
CoRR
Phil-Alexander Hofmann, Damar Wicaksono, Michael Hecht
2025 J jnl
Minterpy: multivariate polynomial interpolation in Python.
J. Open Source Softw.
Damar Wicaksono, Uwe Hernandez Acosta, Sachin Krishnan Thekke Veettil, Jannik Kissinger, Michael Hecht
2025 J jnl
Multivariate Newton Interpolation in Downward Closed Spaces Reaches the Optimal Geometric Approximation Rates for Bos-Levenberg-Trefethen Functions.
CoRR
Michael Hecht, Phil-Alexander Hofmann, Damar Wicaksono, Uwe Hernandez Acosta, Krzysztof Gonciarz, Jannik Kissinger, Vladimir Sivkin, Ivo F. Sbalzarini
2024 J jnl
A note on the rate of convergence of integration schemes for closed surfaces.
Comput. Appl. Math.
Gentian Zavalani, Elima Shehu, Michael Hecht
2024 J jnl
Ensuring Topological Data-Structure Preservation under Autoencoder Compression Due to Latent Space Regularization in Gauss-Legendre Nodes.
Axioms
Chethan Krishnamurthy Ramanaik, Anna Willmann, Juan Esteban Suarez Cardona, Pia Hanfeld, Nico Hoffmann, Michael Hecht
2024 J jnl
High-order numerical integration on regular embedded surfaces.
CoRR
Gentian Zavalani, Michael Hecht
2024 J jnl
Hybrid Surrogate Models: Circumventing Gibbs Phenomenon for Partial Differential Equations with Finite Shock-Type Discontinuities.
CoRR
Juan Esteban Suarez Cardona, Shashank Reddy, Michael Hecht
2024 J jnl
Negative order sobolev cubatures: preconditioners of partial differential equation learning tasks circumventing numerical stiffness.
Mach. Learn. Sci. Technol.
Juan Esteban Suarez Cardona, Phil-Alexander Hofmann, Michael Hecht
2024 J jnl
PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates.
CoRR
Janina Schreiber, Pau Batlle, Damar Wicaksono, Michael Hecht
2023 J jnl
Ensuring Topological Data-Structure Preservation under Autoencoder Compression due to Latent Space Regularization in Gauss-Legendre nodes.
CoRR
Chethan Krishnamurthy Ramanaik, Juan Esteban Suarez Cardona, Anna Willmann, Pia Hanfeld, Nico Hoffmann, Michael Hecht
2023 J jnl
Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces.
SIAM J. Sci. Comput.
Sachin K. Thekke Veettil, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, Michael Hecht
2023 J jnl
High-Order Integration on regular triangulated manifolds reaches Super-Algebraic Approximation Rates through Cubical Re-parameterizations.
CoRR
Gentian Zavalani, Oliver Sander, Michael Hecht
2023 J jnl
Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces.
CoRR
Juan Esteban Suarez Cardona, Phil-Alexander Hofmann, Michael Hecht
2023 — conf
Minimizing Black Boxes due to Polynomial-Model-Based Optimization.
GECCO Companion
Janina Schreiber, Damar Wicaksono, Michael Hecht
2023 J jnl
Polynomial differentiation decreases the training time complexity of physics-informed neural networks and strengthens their approximation power.
Mach. Learn. Sci. Technol.
Juan Esteban Suarez Cardona, Michael Hecht
2023 J jnl
Polynomial-Model-Based Optimization for Blackbox Objectives.
CoRR
Janina Schreiber, Damar Wicaksono, Michael Hecht
2023 J jnl
UQTestFuns: A Python3 library of uncertainty quantification (UQ) test functions.
J. Open Source Softw.
Damar Wicaksono, Michael Hecht
2022 J jnl
Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces.
CoRR
Sachin K. Thekke Veettil, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, Michael Hecht
2022 J jnl
Multivariate Polynomial Regression of Euclidean Degree Extends the Stability for Fast Approximations of Trefethen Functions.
CoRR
Sachin K. Thekke Veettil, Yuxi Zheng, Uwe Hernandez Acosta, Damar Wicaksono, Michael Hecht
2022 J jnl
Replacing Automatic Differentiation by Sobolev Cubatures fastens Physics Informed Neural Nets and strengthens their Approximation Power.
CoRR
Juan Esteban Suarez Cardona, Michael Hecht
2021 J jnl
InFlow: Robust outlier detection utilizing Normalizing Flows.
CoRR
Nishant Kumar, Pia Hanfeld, Michael Hecht, Michael Bussmann, Stefan Gumhold, Nico Hoffmann
2021 J jnl
Tight Localizations of Feedback Sets.
ACM J. Exp. Algorithmics
Michael Hecht, Krzysztof Gonciarz, Szabolcs Horvát
2020 J jnl
Multivariate Interpolation on Unisolvent Nodes - Lifting the Curse of Dimensionality.
CoRR
Michael Hecht, Krzysztof Gonciarz, Jannik Michelfeit, Vladimir Sivkin, Ivo F. Sbalzarini
2020 J jnl
Tight Localizations of Feedback Sets.
CoRR
Michael Hecht, Krzysztof Gonciarz, Szabolcs Horvát
2018 J jnl
Exact Localisations of Feedback Sets.
Theory Comput. Syst.
Michael Hecht
2017 J jnl
A generalization of the most common subgraph distance and its application to graph editing.
Pattern Recognit. Lett.
Michael Hecht
2017 J jnl
Exact Localisations of Feedback Sets.
CoRR
Michael Hecht