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A number of coupling strategies are presented for stochastically modeledbiochemical processes with time-dependent parameters. In particular, thestacked coupling is introduced and is shown via a number of examples to providean exceptionally low variance between the generated paths. This coupling willbe useful in the numerical computation of parametric sensitivities and the fastestimation of expectations via multilevel Monte Carlo methods. We provide therequisite estimators in both cases.

Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions