Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unbiased Filtering of a Class of Partially Observed Diffusions   In this article we consider a Monte Carlo-based method to filter partially
observed diffusions observed at regular and discrete times. Given access only
to Euler discretizations of the diffusion process, we present a new procedure
which can return online estimates of the filtering distribution with no
discretization bias and finite variance. Our approach is based upon a novel
double application of the randomization methods of Rhee & Glynn (2015) along
with the multilevel particle filter (MLPF) approach of Jasra et al (2017). A
numerical comparison of our new approach with the MLPF, on a single processor,
shows that similar errors are possible for a mild increase in computational
cost. However, the new method scales strongly to arbitrarily many processors.

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The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
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The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess