1 citations · 1 across the 3 of their papers we have counts for
4 papers
Local training and enrichment based on a residual localization strategy
Tim Keil, Mario Ohlberger, Felix Schindler +1
To efficiently tackle parametrized multi and/or large scale problems, we propose an adaptive localized model order reduction framework combining both local offline training and loc…
DEIM vs. leverage scores for time-parallel construction of problem-adapted basis functions
Julia Schleuß, Kathrin Smetana
To tackle heterogeneous time-dependent problems, an algorithm that constructs problem-adapted basis functions in an embarrassingly parallel and local manner in time has recently be…
Randomized quasi-optimal local approximation spaces in time
Julia Schleuß, Kathrin Smetana, Lukas ter Maat
We target time-dependent partial differential equations (PDEs) with heterogeneous coefficients in space and time. To tackle these problems, we construct reduced basis/ multiscale a…
Optimal local approximation spaces for parabolic problems
Julia Schleuß, Kathrin Smetana
We propose local space-time approximation spaces for parabolic problems that are optimal in the sense of Kolmogorov and may be employed in multiscale and domain decomposition metho…