I have a question on Bayesian inference with uncertain data. I browsed the tutorial on Bayesian linear regression, and noticed the data used in the tutorial are fixed value, so a MSE loss function can be conveniently used in the inference.
In my case, I also try to perfom Bayesian to get the posterior distribution of my model parameters (the model it self is quite complicated but I assume it would not matter too much in pyro). The difference is that the data I have are from experiments and are uncertain, e.g. ~ N(1.0, 0.1).
I wonder in this case, can I use pyro to perform the Bayesian inference for my model parameter? How can I define a loss function? Any example I can learn from?