High-dimensional Filtering using Nested Sequential Monte Carlo

IEEE Transactions on Signal Processing, 2019.

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Abstract:

Sequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good proposal distribution can perform poorly, in particular in high dimensions. We propose nested sequential Monte Carlo, a methodology that generalizes the SMC framework by requiring only approxim...More

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