RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.
-
Updated
May 23, 2024 - C++
RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.
pyMOR - Model Order Reduction with Python
A Control Systems Toolbox for Julia
Easy Reduced Basis method
Modred main repository
Model reduction library with an emphasis on large scale parallelism and linear subspace methods
Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
MADS: Model Analysis & Decision Support
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.
sssMOR - Sparse State-Space and Model Order Reduction Toolbox
Richards equation on porous media
(MIRROR) Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
Support Vector Regression for Unsupervised Machine Learning
Matlab scripts to recreate figures of the JR Soc Interface article "Model reduction enables Turing instability analysis of large reaction-diffusion models"
emgr -- EMpirical GRamian Framework
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition
Semantic Segmentation with reduced fully convolutional networks for higher latency and lower memory requirement.
Numerical Implementation (Finite Difference) of the Pseudo-two-Dimensional Model for Lithium-ion Batteries
Add a description, image, and links to the model-reduction topic page so that developers can more easily learn about it.
To associate your repository with the model-reduction topic, visit your repo's landing page and select "manage topics."