Computing f-Divergences and Distances of High-Dimensional Probability Density Functions — Low-Rank Tensor Approximations —

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Event: Veröffentlichung

(where): Aachen

(who): Universitätsbibliothek der RWTH Aachen

(when): 2021

Creator: Litvinenko, Alexander
Marzouk, Youssef
Matthies, Hermann G.
Scavino, Marco
Spantini, Alessio

DOI: 10.18154/RWTH-2021-10499

URN: urn:nbn:de:101:1-2021112102261671839820

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:44 PM CET

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Associated

Litvinenko, Alexander
Marzouk, Youssef
Matthies, Hermann G.
Scavino, Marco
Spantini, Alessio
Universitätsbibliothek der RWTH Aachen

Time of origin

2021

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Probability approximations via the Poisson clumping heuristic

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Computing f-Divergences and Distances of High-Dimensional Probability Density Functions — Low-Rank Tensor Approximations —

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Other Objects (12)

Computing f‐divergences and distances of high‐dimensional probability density functions

Asymptotic approximations for probability integrals

Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations

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Asymptotic approximations for probability integrals

Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations

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Probability approximations via the Poisson clumping heuristic

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