79 citations · 258 across the 61 of their papers we have counts for
3 papers · 1 filter
Deep importance sampling using tensor trains with application to a priori and a posteriori rare event estimation
Tiangang Cui, Sergey Dolgov, Robert Scheichl
We propose a deep importance sampling method that is suitable for estimating rare event probabilities in high-dimensional problems. We approximate the optimal importance distributi…
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference
Jakob Kruse, Gianluca Detommaso, Ullrich Köthe +1
Many recent invertible neural architectures are based on coupling block designs where variables are divided in two subsets which serve as inputs of an easily invertible (usually af…
A Stein variational Newton method
Gianluca Detommaso, Tiangang Cui, Alessio Spantini +2
Stein variational gradient descent (SVGD) was recently proposed as a general purpose nonparametric variational inference algorithm [Liu & Wang, NIPS 2016]: it minimizes the Kullbac…