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Matthias Ehrhardt

8 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author4
  • last author1

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • math.DS3
  • math.NA2
  • cs.LG1
  • math-ph1
  • physics.soc-ph1
ORCID 0000-0003-2561-8854
same name
  • Matthias Ehrhardt — 7 papers
  • Matthias Ehrhardt — 2 papers, h 3
  • Matthias Ehrhardt — 2 papers
  • Matthias Ehrhardt — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedPINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss

31 citations · 32 across the 8 of their papers we have counts for

collaborators
Showing math.NAShow all

3 papers · 1 filter

math.NA2025

A Generalized Second-Order Positivity-Preserving Numerical Method for Non-Autonomous Dynamical Systems with Applications

Manh Tuan Hoang, Matthias Ehrhardt

In this work, we propose a generalized, second-order, nonstandard finite difference (NSFD) method for non-autonomous dynamical systems. The proposed method combines the NSFD framew…

math.NA2024

Absorbing Boundary Conditions for Variable Potential Schrödinger Equations via Titchmarsh-Weyl Theory

Matthias Ehrhardt, Chunxiong Zheng

We propose a novel approach to simulate the solution of the time-dependent Schrödinger equation with a general variable potential. The key idea is to approximate the Titchmarsh-Wey…

math.NA2023★ 1 cited

Deep smoothness WENO scheme for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators

Tatiana Kossaczká, Ameya D. Jagtap, Matthias Ehrhardt

In this paper, we introduce an improved version of the fifth-order weighted essentially non-oscillatory (WENO) shock-capturing scheme by incorporating deep learning techniques. The…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.