It’s not so theory heavy but I’ve enjoyed the paper titled “what uncertainty do we need in Bayesian deep learning for computer vision?” By Kendall and Gal of Cambridge.
If you find some nice introductory/theory paper please share them also :)!
Exactly what I was looking for. I have been trying to figure out the best structure for my training and this helps. I have not quite pinpointed what I want to do yet, but I am rebuilding it from the ground up. Speaking of which- any familiarity with ImageJ?