Gradient-based data and parameter dimension reduction for Bayesian
models: an information theoretic perspective

Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective

18 July 2022

Ricardo Baptista

Youssef Marzouk

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Papers citing "Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective"

9 / 9 papers shown

Title
A friendly introduction to triangular transport M. Ramgraber Daniel Sharp M. Le Provost Youssef Marzouk 91 0 0 27 Mar 2025
Dimension reduction via score ratio matching Ricardo Baptista Michael C. Brennan Youssef Marzouk 47 1 0 25 Oct 2024
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity Analysis Qiao Chen Elise Arnaud Ricardo Baptista O. Zahm 109 1 0 19 Jun 2024
Distributed Nonlinear Filtering using Triangular Transport Maps Daniel Grange Ricardo Baptista Amirhossein Taghvaei Allen R. Tannenbaum Sean Phillips 70 1 0 29 Oct 2023
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization M. Le Provost Ricardo Baptista J. Eldredge Youssef Marzouk 43 1 0 12 Oct 2023
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks Sanket Jantre Nathan M. Urban Xiaoning Qian Byung-Jun Yoon BDL UQCV 68 5 0 06 Sep 2023
Principal Feature Detection via $Φ$ -Sobolev Inequalities Matthew T.C. Li Youssef Marzouk O. Zahm 63 9 0 10 May 2023
Ensemble transport smoothing. Part II: Nonlinear updates M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 54 6 0 31 Oct 2022
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning Thomas O'Leary-Roseberry Peng Chen Umberto Villa Omar Ghattas AI4CE 102 42 0 21 Jun 2022