A new reduced-order modeling framework uses tensor-train decomposition of finite element snapshots to cut offline costs and reduce subspace dimensions for parameterized PDEs on Cartesian grids.
Reduced basis approx imation of parametrized optimal flow control problems for the Stokes equations
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A tensor-train reduced basis solver for parameterized partial differential equations on Cartesian grids
A new reduced-order modeling framework uses tensor-train decomposition of finite element snapshots to cut offline costs and reduce subspace dimensions for parameterized PDEs on Cartesian grids.