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Table 1 Effect of the sample size \(N_{s}\) on the maximum relative error in the \(L^{2}\)-norm for the mean and standard deviation obtained from the NIROM-CAEs (\(L_{x}=50\), \(L_{t}=10\)) and POD-ANN (\(\epsilon _{s}=\epsilon _{t}=10^{-8}\)) approaches. Errors are computed with respect to the LHS reference solution (with \(N_{s}=2000\) realizations)

From: Reduced-order modeling for stochastic large-scale and time-dependent flow problems using deep spatial and temporal convolutional autoencoders

\( N_{s} \)

\( L_{POD} \)

\(Err_{L^{2},\,Mean}^{max}\)

\(Err_{L^{2},\,Std}^{max}\)

  

POD-ANN

NIROM-CAEs

POD-ANN

NIROM-CAEs

30

860

8.2855E−07

2.1896E−06

0.024537

0.010349

90

2112

6.0781E−07

9.0018E−07

0.013303

0.005838

300

3387

9.1037E−07

1.9986E−07

0.016687

7.4981E−04