DERLoss#

class torch_uncertainty.losses.DERLoss(reg_weight, reduction='mean')[source]#

The Deep Evidential Regression loss.

This loss combines the negative log-likelihood loss of the normal inverse gamma distribution and a weighted regularization term.

Parameters:

reg_weight (float) – The weight of the regularization term.
reduction (str | None) – Specifies the reduction to apply to the output. Must be one of 'none', 'mean' or 'sum'.

References

[1] Amini, A., Schwarting, W., Soleimany, A., & Rus, D. (2019). Deep evidential regression.