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05/18/2023
Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method
The solution of computational fluid dynamics problems is one of the most...
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03/05/2023
Self-reinforced polynomial approximation methods for concentrated probability densities
Transport map methods offer a powerful statistical learning tool that ca...
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02/16/2023
A weighted subspace exponential kernel for support tensor machines
High-dimensional data in the form of tensors are challenging for kernel ...
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01/20/2023
State-constrained Optimization Problems under Uncertainty: A Tensor Train Approach
We propose an algorithm to solve optimization problems constrained by pa...
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09/05/2022
Deep importance sampling using tensor-trains with application to a priori and a posteriori rare event estimation
We propose a deep importance sampling method that is suitable for estima...
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08/15/2022
Undersampling Raster Scans in Spectromicroscopy for reduced dose and faster measurements
Combinations of spectroscopic analysis and microscopic techniques are us...
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11/09/2021
TTRISK: Tensor Train Decomposition Algorithm for Risk Averse Optimization
This article develops a new algorithm named TTRISK to solve high-dimensi...
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06/08/2021
Conditional Deep Inverse Rosenblatt Transports
We present a novel offline-online method to mitigate the computational b...
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07/31/2020
Functional Tucker approximation using Chebyshev interpolation
This work is concerned with approximating a trivariate function defined ...
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07/14/2020
Deep Composition of Tensor Trains using Squared Inverse Rosenblatt Transports
Characterising intractable high-dimensional random variables is one of t...
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02/12/2020
Efficient Structure-preserving Support Tensor Train Machine
Deploying the multi-relational tensor structure of a high dimensional fe...
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01/22/2020
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format
Low rank tensor approximations have been employed successfully, for exam...
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12/14/2019
Solving differential Riccati equations: A nonlinear space-time method using tensor trains
Differential algebraic Riccati equations are at the heart of many applic...
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08/05/2019
A Tensor Decomposition Approach for High-Dimensional Hamilton-Jacobi-Bellman Equations
A tensor decomposition approach for the solution of high-dimensional, fu...
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04/21/2019
Kriging in Tensor Train data format
Combination of low-tensor rank techniques and the Fast Fourier transform...
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10/02/2018