257 citations · 1.1k across the 33 of their papers we have counts for
4 papers · 1 filter
A weighted subspace exponential kernel for support tensor machines
Kirandeep Kour, Sergey Dolgov, Peter Benner +2
High-dimensional data in the form of tensors are challenging for kernel classification methods. To both reduce the computational complexity and extract informative features, kernel…
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…
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction
Tiangang Cui, Sergey Dolgov, Olivier Zahm
We present a novel offline-online method to mitigate the computational burden of the characterization of posterior random variables in statistical learning. In the offline phase, t…
Deep composition of tensor-trains using squared inverse Rosenblatt transports
Tiangang Cui, Sergey Dolgov
Characterising intractable high-dimensional random variables is one of the fundamental challenges in stochastic computation. The recent surge of transport maps offers a mathematica…