Sensitivity-Driven Adaptive Surrogate Modeling for Simulation and Optimization of Dynamical Systems

Jonathan R. Cangelosi, Matthias Heinkenschloss

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DOI: 10.1137/25m1813469
Published: 2026-09-02
Container: SIAM Journal on Scientific Computing
Publisher: Society for Industrial & Applied Mathematics (SIAM)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1137/25m1813469,
  title = {Sensitivity-Driven Adaptive Surrogate Modeling for Simulation and Optimization of Dynamical Systems},
  author = {Jonathan R. Cangelosi and Matthias Heinkenschloss},
  year = {2026},
  journal = {SIAM Journal on Scientific Computing},
  doi = {10.1137/25m1813469},
  url = {https://doi.org/10.1137/25m1813469}
}

RIS

TY  - JOUR
TI  - Sensitivity-Driven Adaptive Surrogate Modeling for Simulation and Optimization of Dynamical Systems
AU  - Jonathan R. Cangelosi
AU  - Matthias Heinkenschloss
PY  - 2026
JO  - SIAM Journal on Scientific Computing
DO  - 10.1137/25m1813469
UR  - https://doi.org/10.1137/25m1813469
ER  -

APA

Cangelosi, J. R., & Heinkenschloss, M. (2026). Sensitivity-Driven Adaptive Surrogate Modeling for Simulation and Optimization of Dynamical Systems. SIAM Journal on Scientific Computing. https://doi.org/10.1137/25m1813469

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crossref · retrieved 2026-11-06T00:26:23.561Z