Grid methods for Bayes-optimal continuous-discrete filtering and utilizing a functional tensor train representation

DOI10.1080/17415977.2020.1862109zbMath1469.65144OpenAlexW3119822608MaRDI QIDQ5152273

Malcolm E. K. Morrison, Timothy C. A. Molteno, Sergey V. Dolgov, Colin D. Fox

Publication date: 17 September 2021

Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17415977.2020.1862109

zbMATH Keywords

dynamical systemfilteringnumerical solution of partial differential equationstensor trainBayesian sequential inference

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs (65M32) Numerical linear algebra (65F99)

Uses Software

• Matlab

Cites Work

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• Tensor-Train Decomposition
• TT-cross approximation for multidimensional arrays
• Chaos, fractals, and noise: Stochastic aspects of dynamics.
• A theory of pseudoskeleton approximations
• Constructive representation of functions in low-rank tensor formats
• Approximation and sampling of multivariate probability distributions in the tensor train decomposition
• A tensor decomposition algorithm for large ODEs with conservation laws
• DMRG approach to fast linear algebra in the TT-format
• Stochastic processes and filtering theory
• Parallel cross interpolation for high-precision calculation of high-dimensional integrals
• Spectral Methods in MATLAB
• Numerical Approximation of the Frobenius--Perron Operator using the Finite Volume Method

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