Table 4 Burgers’ problem: hyperparameters for the TCN network
From: Deep convolutional architectures for extrapolative forecasts in time-dependent flow problems
Hyperparameters | Values |
|---|---|
Sequence length (\(n_t\)) | 5, 10, 20 |
TCN block channels | [32, 32], [64, 64], [32, 32, 32], [64,64,64] |
Latent dimension (m) | 12, 25, 50 |
Kernel size (k) | 3, 5, 7, 9 |
Activation | tanh |
Loss function | MSE |
Learning rate | \(1 \times 10^{-4}\) |
Max model parameter (\(n_t = 10\), \(m = 50\)) | 78,322 |
Min model parameters (\(n_t = 10\), \(m = 50\)) | 17,554 |