Surrogates UCL
==============

.. dropdown:: :doc:`TN-01_ReportSuitabilityPotentialRomFusionANonIntrusiveRomSolversHighDimensionalOutputs`

    This report discusses the challenges of efficient uncertainty quantification in modern physical computer models and proposes a non-intrusive reduced order model (ROM) using Gaussian process (GP) surrogates for problems with high dimensional outputs. The method is applied to an anisotropic heat transport problem.

.. dropdown:: :doc:`TN-02_ReportSuitabilityPotentialReducedOrderModellingRomFusionModels`

    This report explores the suitability and potential of Reduced Order Modelling (ROM) in fusion models, specifically focusing on Gaussian Process ROM for Solvers with High-dimensional Outputs.


.. toctree::
    :hidden:
    :caption: Contents:
    TN-01_ReportSuitabilityPotentialRomFusionANonIntrusiveRomSolversHighDimensionalOutputs.rst
    TN-02_ReportSuitabilityPotentialReducedOrderModellingRomFusionModels.rst