• Corpus ID: 246285493

A Kernel Learning Method for Backward SDE Filter

@article{Archibald2022AKL,
  title={A Kernel Learning Method for Backward SDE Filter},
  author={Richard Archibald and Feng Bao},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.10600}
}
In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. To characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous… 
A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems
TLDR
An adaptive kernel method is introduced to adaptively construct Gaussian kernels to approximate the probability distribution of the target state of a target stochastic dynamical system based on partial noisy observational data.

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