15 citations · 30 across the 6 of their papers we have counts for
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stat.ML2021★ 4 cited
Stein Variational Gradient Descent: many-particle and long-time asymptotics
Nikolas Nüsken, D. R. Michiel Renger
Stein variational gradient descent (SVGD) refers to a class of methods for Bayesian inference based on interacting particle systems. In this paper, we consider the originally propo…
stat.ML2021★ 8 cited
Solving high-dimensional parabolic PDEs using the tensor train format
Lorenz Richter, Leon Sallandt, Nikolas Nüsken
High-dimensional partial differential equations (PDEs) are ubiquitous in economics, science and engineering. However, their numerical treatment poses formidable challenges since tr…