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, optional) – specifies the reduction to apply to the output:
'none'
|'mean'
|'sum'
.
References
[1] Amini, A., Schwarting, W., Soleimany, A., & Rus, D. (2019). Deep evidential regression.