pyMOR - Model Order Reduction with Python

Modred main repository

Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.

AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)

Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" by S. A. McQuarrie, C. Huang, and K. E. Willcox.

AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control

Semantic Segmentation with reduced fully convolutional networks for higher latency and lower memory requirement.

Python implementation of the shifted proper orthogonal decomposition

Source code for the paper "Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference" by McQuarrie, Khodabakhshi, and Willcox

Supplemental Material for "BUQEYE Guide to Projection-Based Emulators in Nuclear Physics"

System-Theoretic Model Order Reduction in Python

Nonlinear model reduction for operator learning

Model Reduction of the Approximate Master Equation for Epidemic Processes on Complex Networks