To compare the EA and debiasing approaches, we use the same setup as the 1D example. The 95% confidence interval from the EA approach for x = (0 . 2 , 0 . 2) T is (5 . 29 ± 0 . 01) × 10 − $^{2}$, and from the debiasing approach is (5 . 49 ± 0 . 39) × 10 − $^{2}$. The average time per estimate was 0.185 seconds for the EA approach, and 0.662 seconds for the debiasing approach. For x = (0 . 8 , 0 . 8) T the 95% confidence intervals were (6 . 81 ± 0 . 001) × 10 − 1 for EA and (6 . 84 ± 0 . 21) × 10 − 1 for debiasing, with average computation times per estimate of 0.126 s for EA, and 0.977 for debiasing. As with the 1D example, the EA approach gives lower variance estimators with a lower com- putational expense. In this paper we have demonstrated how the FKF, combined with recent 6. Conclusions 25 Figure 1: Estimates of the FKF for the 2D PDE model at t = 2, x = c (0 . 2 , 0 . 2) T (left), and t = 2, x = c (0 . 8 , 0 . 8) T (right). In each case the Euler- Maruyama approximation (points) converges to the EA estimate (horizontal line). 0.05 0.10 0.15 0.20 0.25 Intervals per unit time Estimate 2 0 2 2 4 2 6 2 8 2 10 2 12 2 14 2 16 2 18 Intervals per unit time Estimate 2 0 2 2 4 2 6 2 8 2 10 2 12 2 14 2 16 2 18 0.65 0.75 0.85 0.95 1.05