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Table 9 Performance boost of GP-PINN on the Helmholtz benchmarks using transfer learning

From: Transfer learning for deep neural network-based partial differential equations solving

Subtask Original Transfer Boost
case 2 9.01e-03 6.51e-03 27.7%
case 3 3.48e-03 3.30e-03 5.2%
case 4 9.20e-03 6.14e-03 33.3%
case 5 2.33e-02 1.89e-02 18.9%
case 6 3.04e-02 2.75e-02 9.5%
case 7 7.28e-02 3.71e-02 49.0%
case 8 8.59e-01 8.23e-02 90.4%