ggt.losses.aleatoric_cov_loss
Module Contents
Functions
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Computes the Aleatoric Loss while including the full |
- ggt.losses.aleatoric_cov_loss.aleatoric_cov_loss(outputs, targets, num_var=3, average=True)
Computes the Aleatoric Loss while including the full covariance matrix of the outputs.
If you are predicting for n output variables, then the number of output neuros required for this loss is (3n + n^2)/2.
- Args:
outputs: (tensor) - predicted outputs from the model targets: (tensor) - ground truth labels size_average: (bool) - if True, the losses are
averaged over all elements of the batch
- Returns:
aleatoric_cov_loss: (tensor) - aleatoric loss
- Formula:
- loss = 0.5 * [Y - Y_hat].T * cov_mat_inv
[Y - Y_hat] + 0.5 * log(det(cov_mat))