257 citations · 1.1k across the 33 of their papers we have counts for
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Functional Tucker approximation using Chebyshev interpolation
Sergey Dolgov, Daniel Kressner, Christoph Strössner
This work is concerned with approximating a trivariate function defined on a tensor-product domain via function evaluations. Combining tensorized Chebyshev interpolation with a Tuc…
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…
Efficient Structure-preserving Support Tensor Train Machine
Kirandeep Kour, Sergey Dolgov, Martin Stoll +1
An increasing amount of collected data are high-dimensional multi-way arrays (tensors), and it is crucial for efficient learning algorithms to exploit this tensorial structure as m…
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format
Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck +1
Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up lar…