Mean Squared Error

Lambda Key: lambda_mse

Mean Squared Error (MSE) loss function. The MSE loss function is defined as:

\[\mathcal{L}_{mse} = \frac{\lambda_{mse}}{B \times T \times N_{out}} \sum_{b,t,k=0}^{B, T, N_{out}} \left( \hat{y}_{b,t,k} - y_{b,t,k} \right)^2\]
  • $ B $: number of batches.
  • $ T $: number of time steps.
  • $ N_{out} $: dimension of the outputs.
  • \(\hat{y}_{b,t,k}\) is the predicted value of batch $b$, timepoint $t$, dimension $d$.
  • $y_{b,t,k}$ is the ground truth value of batch $b$, timepoint $t$, dimension $d$.

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