pyMOR - Model Order Reduction with Python
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Updated
Nov 20, 2024 - Python
pyMOR - Model Order Reduction with Python
RBniCS - reduced order modelling in FEniCS (legacy)
Easy Reduced Basis method
ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis
High-level model-order reduction to automate the acceleration of large-scale simulations
sssMOR - Sparse State-Space and Model Order Reduction Toolbox
GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.
emgr -- EMpirical GRamian Framework
The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-uniform parameter/time-varying grid, such that the Kolmogorov n-width of the mapped data on the learned grid is minimized.
Python tools for non-intrusive reduced order modeling
morgen - Model Order Reduction for Gas and Energy Networks
Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow water equations
HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition
Python libraries (NumPy-based) to perform model order reduction, clustering and data analysis for combustion and aerothermochemistry data
Python code of the paper Model order reduction of deep structured state-space models: A system-theoretic approach
PROTON - A Python Framework for Physics-Based Electromigration Assessment on Contemporary VLSI Power Grids
RBniCSx - reduced order modelling in FEniCSx
Neural Ordinary Differential Equations for model order reduction of time-dependent PDEs
Supporting code for "reduced order modeling using advection-aware autoencoders"
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