Fetching the paper…
Reading the bibliography…
The nonlinear filtering problem is concerned with finding the conditional probability distribution (posterior) of the state of a stochastic dynamical system, given a history of partial and noisy observations.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
Earlier work this paper cites.
Deterministic nonperiodic flow
Edward N Lorenz · 1963
Earlier work this paper cites.
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Neil J Gordon, David J Salmond, and Adrian FM Smith · 1993
Earlier work this paper cites.
On the stability of interacting processes with applications to filtering and genetic algorithms
Pierre Del Moral and Alice Guionnet · 2001
Earlier work this paper cites.
The ensemble Kalman filter: Theoretical formulation and practical implementation
Geir Evensen · 2003
Earlier work this paper cites.
Topics in optimal transportation
Cédric Villani · 2003
Earlier work this paper cites.
Estimation with applications to tracking and navigation: theory algorithms and software
Yaakov Bar-Shalom, X Rong Li, and Thiagalingam Kirubarajan · 2004
Earlier work this paper cites.
A kernel method for the two-sample-problem
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, and Alex Smola · 2006
Earlier work this paper cites.
Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems
Thomas Bengtsson, Peter Bickel, and Bo Li · 2008
Earlier work this paper cites.
Sharp failure rates for the bootstrap particle filter in high dimensions
Peter Bickel, Bo Li, Thomas Bengtsson, et al · 2008
Earlier work this paper cites.
Inference in hidden Markov models
Olivier Cappé, Eric Moulines, and Tobias Rydén · 2009
Earlier work this paper cites.
A tutorial on particle filtering and smoothing: Fifteen years later
Arnaud Doucet and Adam M Johansen · 2009
Earlier work this paper cites.
Data Assimilation: The Ensemble Kalman Filter
Geir Evensen · 2009
Earlier work this paper cites.
Observability and nonlinear filtering
Ramon Van Handel · 2009
Cited alongside, same era.
Uniform observability of hidden Markov models and filter stability for unstable signals
Ramon Van Handel · 2009
Cited alongside, same era.
Exact particle flow for nonlinear filters
Fred Daum, Jim Huang, and Arjang Noushin · 2010
Cited alongside, same era.
The Oxford handbook of nonlinear filtering
Dan Crisan and Boris Rozovskii · 2011
Cited alongside, same era.
A nonparametric ensemble transform method for Bayesian inference
Sebastian Reich · 2013
Cited alongside, same era.
Feedback particle filter
Tao Yang, Prashant G Mehta, and Sean P Meyn · 2013
Cited alongside, same era.
Optimal transport map estimation in general function spaces
Vincent Divol, Jonathan Niles-Weed, and Aram-Alexandre Pooladian · 2022
Later among the works it cites.
Conditional simulation using diffusion Schrödinger bridges
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, and Arnaud Doucet · 2022
Later among the works it cites.
Coupling techniques for nonlinear ensemble filtering
Alessio Spantini, Ricardo Baptista, and Youssef Marzouk · 2022
Later among the works it cites.
An optimal transport formulation of Bayes’ law for nonlinear filtering algorithms
Amirhossein Taghvaei and Bamdad Hosseini · 2022
Later among the works it cites.
Optimal transport particle filters
Mohammad Al-Jarrah, Bamdad Hosseini, and Amirhossein Taghvaei · 2023
Later among the works it cites.
Optimal transport-based nonlinear filtering in high-dimensional settings
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Flávio Eler De Melo, Simon Maskell, Matteo Fasiolo, and Fred Daum · 2015
Cited alongside, same era.
Can local particle filters beat the curse of dimensionality?
Patrick Rebeschini and Ramon Van Handel · 2015
Cited alongside, same era.
Vector quantile regression: an optimal transport approach
Guillaume Carlier, Victor Chernozhukov, and Alfred Galichon · 2016
Cited alongside, same era.
Sampling via measure transport: An introduction, in Handbook of Uncertainty Quantification
Youssef Marzouk, Tarek Moselhy, Matthew Parno, and Alessio Spantini · 2016
Cited alongside, same era.
Multivariable feedback particle filter
Tao Yang, Richard S Laugesen, Prashant G Mehta, and Sean P Meyn · 2016
Cited alongside, same era.
Ensemble Kalman methods: a mean field perspective
Edoardo Calvello, Sebastian Reich, and Andrew M Stuart · 2022
Cited alongside, same era.
Mohammad Al-Jarrah, Niyizhen Jin, Bamdad Hosseini, and Amirhossein Taghvaei · 2023
Later among the works it cites.
An approximation theory framework for measure-transport sampling algorithms
Ricardo Baptista, Bamdad Hosseini, Nikola B Kovachki, Youssef M Marzouk, and Amir Sagiv · 2023
Later among the works it cites.
Computational optimal transport and filtering on Riemannian manifolds
Daniel Grange, Mohammad Al-Jarrah, Ricardo Baptista, Amirhossein Taghvaei, Tryphon T Georgiou, Sean Phillips, and Allen Tannenbaum · 2023
Later among the works it cites.
Conditional optimal transport on function spaces
Bamdad Hosseini, Alexander W Hsu, and Amirhossein Taghvaei · 2023
Later among the works it cites.
Duality for nonlinear filtering i: Observability
Jin W Kim and Prashant G Mehta · 2023
Later among the works it cites.
Conditional sampling with monotone GANs: from generative models to likelihood-free inference
Nikola Kovachki, Ricardo Baptista, Bamdad Hosseini, and Youssef Marzouk · 2023
Later among the works it cites.
A survey of feedback particle filter and related controlled interacting particle systems (CIPS)
Amirhossein Taghvaei and Prashant G Mehta · 2023
Later among the works it cites.