Hello there,
I am currently working on a project that involves implementing Bayesian neural networks using Pyro, and I’ve encountered a few challenges along the way. I was hoping to seek some guidance and advice from the experienced members of this community.
Specifically, I’m interested in understanding the best practices for setting up the model architecture, defining priors, and incorporating uncertainty estimation into the training process effectively. Additionally, I’m curious about any recommended resources or tutorials that delve into Bayesian neural networks within the Pyro framework.
https://stackoverflow.com/questions/73986450/how-to-make-prediction-in-bayesian-convolutional-neural-network-using-pyro-and-pinfo
Furthermore, if anyone has experience with applying Bayesian methods in real-world scenarios or can share insights on the advantages and limitations of Bayesian neural networks compared to traditional neural networks, I would greatly appreciate your input.
Thankyou in advance.