# Parametric model order reduction using pyMOR

arXiv: https://arxiv.org/abs/2003.05825 · HTML: https://mlsanity.com/paper/2003.05825/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems](https://mlsanity.com/paper/2306.06174/) (2023)

## Abstract (arXiv)

pyMOR is a free software library for model order reduction that includes both reduced basis and system-theoretic methods. All methods are implemented in terms of abstract vector and operator interfaces, which allows direct integration of pyMOR's algorithms with a wide array of external PDE solvers. In this contribution, we give a brief overview of the available methods and experimentally compare them for the parametric instationary thermal-block benchmark defined in arXiv:2003.00846.