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07/09/2023
A generative flow for conditional sampling via optimal transport
Sampling conditional distributions is a fundamental task for Bayesian in...
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05/24/2023
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
We introduce a two-stage probabilistic framework for statistical downsca...
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02/27/2023
An Approximation Theory Framework for Measure-Transport Sampling Algorithms
This article presents a general approximation-theoretic framework to ana...
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02/14/2023
Score-based Diffusion Models in Function Space
Diffusion models have recently emerged as a powerful framework for gener...
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10/31/2022
Ensemble transport smoothing – Part 2: nonlinear updates
Smoothing is a specialized form of Bayesian inference for state-space mo...
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10/31/2022
Ensemble transport smoothing – Part 1: unified framework
Smoothers are algorithms for Bayesian time series re-analysis. Most oper...
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07/18/2022
Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective
We consider the problem of reducing the dimensions of parameters and dat...
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06/22/2022
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
We consider the Bayesian calibration of models describing the phenomenon...
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03/10/2022
A low-rank ensemble Kalman filter for elliptic observations
We propose a regularization method for ensemble Kalman filtering (EnKF) ...
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07/08/2021
Diagonal Nonlinear Transformations Preserve Structure in Covariance and Precision Matrices
For a multivariate normal distribution, the sparsity of the covariance a...
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01/08/2021
Learning non-Gaussian graphical models via Hessian scores and triangular transport
Undirected probabilistic graphical models represent the conditional depe...
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09/22/2020
An adaptive transport framework for joint and conditional density estimation
We propose a general framework to robustly characterize joint and condit...
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06/11/2020
Conditional Sampling With Monotone GANs
We present a new approach for sampling conditional measures that enables...
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06/30/2019
Coupling techniques for nonlinear ensemble filtering
We consider filtering in high-dimensional non-Gaussian state-space model...
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06/22/2018
Bayesian Optimization of Combinatorial Structures
The optimization of expensive-to-evaluate black-box functions over combi...
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11/02/2017