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.

SOFA Plugin to Reduce Model

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

PROTON - A Python Framework for Physics-Based Electromigration Assessment on Contemporary VLSI Power Grids

Python code of the paper Model order reduction of deep structured state-space models: A system-theoretic approach

RBniCSx - reduced order modelling in FEniCSx

Graph Feedforward Networks: a resolution-invariant generalisation of feedforward networks for graphical data, applied to model order reduction

Neural Ordinary Differential Equations for model order reduction of time-dependent PDEs