Dimension reduced surrogate construction for parametric PDE maps
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Updated
Aug 6, 2024 - Python
Dimension reduced surrogate construction for parametric PDE maps
Non-intrusive reduced-order modeling with geometry-informed snapshots. Current based registration is applied to compute the diffeomorphism between snapshots.
Parallel-in-time integration of Neural ODEs with reduced basis approximation
One-dimensional unsteady compressible reacting flow simulation framework, designed for simple prototyping and testing of novel reduced-order model methods.
Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. Available on doi.org/10.1016/j.cma.2021.114181.
Supplemental Material for "BUQEYE Guide to Projection-Based Emulators in Nuclear Physics"
Framework to learn effective dynamics and couple a macro scale simulator with a fast neural network latent propagator.
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
Code TMA4900 Industrial Mathematics, Master’s Thesis
Code for building a reduced-order model for the linear elasticity equation on a square in 2D for my specialization Project at NTNU.
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