activity
20192021
most citedVariational approach to rare event simulation using least-squares regression

22 citations · 28 across the 4 of their papers we have counts for

collaborators

5 papers

math.ST20214 cited

Nonasymptotic bounds for suboptimal importance sampling

Carsten Hartmann, Lorenz Richter

Importance sampling is a popular variance reduction method for Monte Carlo estimation, where a notorious question is how to design good proposal distributions. While in most cases…

stat.ML2021

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…

stat.ML20202 cited

VarGrad: A Low-Variance Gradient Estimator for Variational Inference

Lorenz Richter, Ayman Boustati, Nikolas Nüsken +2

We analyse the properties of an unbiased gradient estimator of the ELBO for variational inference, based on the score function method with leave-one-out control variates. We show t…

math.OC2020

Model Order Reduction for (Stochastic-) Delay Equations With Error Bounds

Simon Becker, Lorenz Richter

We analyze a structure-preserving model order reduction technique for delay and stochastic delay equations based on the balanced truncation method and provide a system theoretic in…

math.PR201922 cited

Variational approach to rare event simulation using least-squares regression

Carsten Hartmann, Omar Kebiri, Lara Neureither +1

We propose an adaptive importance sampling scheme for the simulation of rare events when the underlying dynamics is given by a diffusion. The scheme is based on a Gibbs variational…