Official Release of the RAVEN code.
Version: 2.3

• RAVEN USER MANUAL
• RAVEN USER GUIDE
• RAVEN THEORY MANUAL
• REGRESSION TEST DOCUMENTATION
• ANALYTICAL TEST DOCUMENTATION
• RAVEN PLUGIN MANUAL

Importance Features:

• Addition of a new ROM "augmentation" for the online feature selection. Two algorithms have been added (#1301):
  • RFE, Recursive Feature Elimination (augmented with several new algorithms and customization)
  • VarianceThreshold, which removes the features whose variance is < a user-defined threshold.
  In addition, a dimensionality reduction technique to "uncorrelate" the feature space has been added as well, such as PCA, KernelPCA, ICA
• Adding Simulate (https://www.studsvik.com/what-we-do/products/simulate5/) code interface (#1992)

Experimental Features:

• Use Mamba to install RAVEN which can accelerate the installation process:
  ./scripts/establish_conda_env.sh --mamba

• Use “pip” to install RAVEN (https://pypi.org/project/raven-framework/)
  pip install raven-framework
  These should work on Linux, Mac OS and Windows. After installation, the raven_framework command can be used to run raven.

Other Features:

• Allow optimizers to be initialized with Custom Sampler #2084
• Adds the ability for a DataSet to have an automatically generated index. #2093
• Hausdorff Similarity Measure for Genetic Convergence #2032

Submodule Updates:
The updates for the submodules are tracked by issue #1114. In this release, there are significant updates in following Plugins. We recommend the users to check the following links for more details.
TEAL: https://github.com/idaholab/TEAL
HERON: https://github.com/idaholab/HERON
SR2ML: https://github.com/idaholab/SR2ML
LOGOS: https://github.com/idaholab/LOGOS
FARM: https://github.com/Argonne-National-Laboratory/FARM

Addressed Defects:
#2095
#2086
#2076
#2079
#2089
#1778
#2073
#2064
#2035
#2057
#1803
#1742
#1757
#1741
#1699
#1869
#2040
#2031
#2034
#2030
#2036
#2028
#1982
#2007
#1915
#2006
#2009
#1870
#1968

Internal Developer:
We would like to thank all RAVEN internal developers for their significant contributions, including but not limit to: @wangcj05 @mandd @PaulTalbot-INL @joshua-cogliati-inl @Jimmy-INL @dylanjm @dgarrett622 @JunyungKim @worseliz @yoshiurr-INL

External Contribution:
We would like to thank all RAVEN external contributors for their significant contributions, including but not limit to @aalfonsi @wanghy-anl