Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unbiased simulation of stochastic differential equations   We propose an unbiased Monte-Carlo estimator for $\mathbb{E}[g(X_{t_1},
\cdots, X_{t_n})]$, where $X$ is a diffusion process defined by a
multi-dimensional stochastic differential equation (SDE). The main idea is to
start instead from a well-chosen simulatable SDE whose coefficients are updated
at independent exponential times. Such a simulatable process can be viewed as a
regime-switching SDE, or as a branching diffusion process with one single
living particle at all times. In order to compensate for the change of the
coefficients of the SDE, our main representation result relies on the automatic
differentiation technique induced by Bismu-Elworthy-Li formula from Malliavin
calculus, as exploited by Fourni\'e et al.(1999) for the simulation of the
Greeks in financial applications. In particular, this algorithm can be
considered as a variation of the (infinite variance) estimator obtained in
Bally and Kohatsu-Higa [Section 6.1](2014) as an application of the parametrix
method.

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The categories of this paper are: physics
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
1
The categories of this paper are: cs
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
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The categories of this paper are: quant-ph
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The categories of this paper are: gr-qc