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math.NA2024
A convergent adaptive finite element stochastic Galerkin method based on multilevel expansions of random fields
Markus Bachmayr, Martin Eigel, Henrik Eisenmann +1
The subject of this work is an adaptive stochastic Galerkin finite element method for parametric or random elliptic partial differential equations, which generates sparse product p…
stat.ML2024
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations
David Sommer, Robert Gruhlke, Max Kirstein +2
Sampling from probability densities is a common challenge in fields such as Uncertainty Quantification (UQ) and Generative Modelling (GM). In GM in particular, the use of reverse-t…