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20162026
most citedA layered multiple importance sampling scheme for focused optimal Bayesian experimental design

14 citations · 39 across the 20 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

stat.ME2023★ 1 cited

A transport approach to sequential simulation-based inference

Paul-Baptiste Rubio, Youssef Marzouk, Matthew Parno

We present a new transport-based approach to efficiently perform sequential Bayesian inference of static model parameters. The strategy is based on the extraction of conditional di…

stat.CO2023★ 5 cited

Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices

Aimee Maurais, Terrence Alsup, Benjamin Peherstorfer +1

We introduce a multifidelity estimator of covariance matrices formulated as the solution to a regression problem on the manifold of symmetric positive definite matrices. The estima…

stat.CO2023

Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty

Friedrich Menhorn, Gianluca Geraci, D. Thomas Seidl +3

Optimization is a key tool for scientific and engineering applications, however, in the presence of models affected by uncertainty, the optimization formulation needs to be extende…

math.ST2023

Score Operator Newton transport

Nisha Chandramoorthy, Florian Schaefer, Youssef Marzouk

We propose a new approach for sampling and Bayesian computation that uses the score of the target distribution to construct a transport from a given reference distribution to the t…

stat.CO2023

Principal Feature Detection via -Sobolev Inequalities

Matthew T. C. Li, Youssef Marzouk, Olivier Zahm

We investigate the approximation of high-dimensional target measures as low-dimensional updates of a dominating reference measure. This approximation class replaces the associated…

stat.ML2023

Diffusion map particle systems for generative modeling

Fengyi Li, Youssef Marzouk

We propose a novel diffusion map particle system (DMPS) for generative modeling, based on diffusion maps and Laplacian-adjusted Wasserstein gradient descent (LAWGD). Diffusion maps…