http://hn.vernccvbvyi5qhfzyqengccj7lkove6bjot2xhh5kajhwvidqafczrad.onion/stories/38519277
I'm a huge advocate for methods that natively incorporate uncertainty, but there are lots of model types that empirically produce very useful results but where it's not obvious how to produce/interpret useful estimates of uncertainty in any sort of efficient manner. Another, separate, issue that is often neglected is the idea of calibrated model outputs, but that's its own rabbit hole. marcyb5st 2y Well, in reality tools like Tensorflow probability can help you model both...