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03/22/2022
An Optimal Transport Formulation of Bayes' Law for Nonlinear Filtering Algorithms
This paper presents a variational representation of the Bayes' law using...
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12/04/2021
Variational Wasserstein gradient flow
The gradient flow of a function over the space of probability densities ...
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06/19/2021
Stein particle filtering
We present a new particle filtering algorithm for nonlinear systems in t...
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10/02/2020
Deep FPF: Gain function approximation in high-dimensional setting
In this paper, we present a novel approach to approximate the gain funct...
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07/08/2020
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Wasserstein Barycenter is a principled approach to represent the weighte...
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05/19/2020
Lasso formulation of the shortest path problem
The shortest path problem is formulated as an l_1-regularized regression...
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10/05/2019
An Optimal Transport Formulation of the Ensemble Kalman Filter
Controlled interacting particle systems such as the ensemble Kalman filt...
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08/28/2019
Optimal transport mapping via input convex neural networks
In this paper, we present a novel and principled approach to learn the o...
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02/19/2019
Gain function approximation in the Feedback Particle Filter
This paper is concerned with numerical algorithms for the problem of gai...
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02/19/2019
2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs
We provide a framework to approximate the 2-Wasserstein distance and the...
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01/10/2019
Accelerated Flow for Probability distributions
This paper presents a methodology and numerical algorithms for construct...
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05/20/2016