Nonlinear model reduction for operator learning
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Updated
Mar 27, 2024 - Python
Nonlinear model reduction for operator learning
System-Theoretic Model Order Reduction in Python
Model Reduction of the Approximate Master Equation for Epidemic Processes on Complex Networks
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"
Python implementation of the shifted proper orthogonal decomposition
Semantic Segmentation with reduced fully convolutional networks for higher latency and lower memory requirement.
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
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: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
Modred main repository
pyMOR - Model Order Reduction with Python
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