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cs.LG2024
Sampling from Boltzmann densities with physics informed low-rank formats
Paul Hagemann, Janina Schütte, David Sommer +2
Our method proposes the efficient generation of samples from an unnormalized Boltzmann density by solving the underlying continuity equation in the low-rank tensor train (TT) forma…
cs.LG2024
Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
Janina Enrica Schütte, Martin Eigel
A neural network architecture is presented that exploits the multilevel properties of high-dimensional parameter-dependent partial differential equations, enabling an efficient app…