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.
Space–time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
math.NA 1years
2024 1verdicts
CONDITIONAL 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
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.