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.
An algebraic least squares reduced basis method for the solution of nonaffinely parametrized 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.