Bernd Röhrig
[The Diagnostic Test: Goodness, Characteristics, and Interpretation: Under the Impact of the Corona Pandemic and Different SARS-CoV-2 Tests]
Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
paper apply machinelearning approach learn traveling solitary waves across various physical systems described families partial differential equations pdes approach integrates novel interpretable neural network nn architecture called separable gaussian neural networks sgnn framework physicsinformed neural networks pinns unlike traditional pinns treat spatial temporal data independent inputs present method leverages wave characteristics transform data socalled cotraveling wave frame reformulation effectively addresses issue propagation failure pinns applied large computational domains sgnn architecture demonstrates robust approximation capabilities singlepeakon multipeakon stationary solutions known leftons within 11dimensional bfamily pdes addition expand investigations explore peakon solutions abfamily also compacton solutions 21dimensional rosenauhyman family pdes comparative analysis multilayer perceptron mlp reveals sgnn achieves comparable accuracy fewer tenth neurons underscoring efficiency potential broader application solving complex nonlinear pdes