2 ms·
In Christopher Bishop’s PRML book, he shows a procedure for getting the full posterior of a neural net using estimates of the Hessian evaluated at the point of
by jl2718 8y ago
In Christopher Bishop’s PRML book, he shows a procedure for getting the full posterior of a neural net using estimates of the Hessian evaluated at the point of inference.
Any idea how sampling compares in performance and computational efficiency?
- program_whiz 8y agoSVI still uses sampling under the hood. Any probabalistic programming framework (such as pyro) uses random sampling, there's no other way to estimate the curves of a complex set of interacting probability distributions. Obviously there are some optimizations for simple distributions that are known (e.g. we know what the expected values of simple gaussians will be, and the PDF or CDF of a given sample).