458 citations · 2.3k across the 71 of their papers we have counts for
8 papers · 1 filter
Ensemble transport smoothing. Part II: Nonlinear updates
Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin +1
Smoothing is a specialized form of Bayesian inference for state-space models that characterizes the posterior distribution of a collection of states given an associated sequence of…
Ensemble transport smoothing. Part I: Unified framework
Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin +1
Smoothers are algorithms for Bayesian time series re-analysis. Most operational smoothers rely either on affine Kalman-type transformations or on sequential importance sampling. Th…
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…
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…
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
Ricardo Baptista, Lianghao Cao, Joshua Chen +4
We consider the Bayesian calibration of models describing the phenomenon of block copolymer (BCP) self-assembly using image data produced by microscopy or X-ray scattering techniqu…
Distributionally Robust Gaussian Process Regression and Bayesian Inverse Problems
Xuhui Zhang, Jose Blanchet, Youssef Marzouk +2
We study a distributionally robust optimization formulation (i.e., a min-max game) for two representative problems in Bayesian nonparametric estimation: Gaussian process regression…