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stat.CO2022★ 2 cited
Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective
Ricardo Baptista, Youssef Marzouk, Olivier Zahm
We consider the problem of reducing the dimensions of parameters and data in non-Gaussian Bayesian inference problems. Our goal is to identify an "informed" subspace of the paramet…
math.ST2022★ 1 cited
On minimax density estimation via measure transport
Sven Wang, Youssef Marzouk
We study the convergence properties, in Hellinger and related distances, of nonparametric density estimators based on measure transport. These estimators represent the measure of i…