I'm using a couple of Bayesian linear layers at the end of a model for regression analysis.
One thing that I noticed is that I have a few samples (within the red circle) with a large prediction error but the model is very certain about these predictions. Wouldn't it make more sense if the model had predicted these samples with large error bars (i.e. high uncertainty)?
I'm using n_samples = 25 when computing std and means during inference.
Is there a way to have high uncertainty for such predictions?
Thanks, @piEsposito for the amazing library.
I'm using a couple of Bayesian linear layers at the end of a model for regression analysis.
One thing that I noticed is that I have a few samples (within the red circle) with a large prediction error but the model is very certain about these predictions. Wouldn't it make more sense if the model had predicted these samples with large error bars (i.e. high uncertainty)?
I'm using
n_samples = 25
when computing std and means during inference.Is there a way to have high uncertainty for such predictions?