Hello,
I would like to point out this link for discussion in this forum before eventually publishing the results.
The topic is the following : it is a new method to our knowledge to produce samples for Monte-Carlo methods that we use also for PDE (Partial Differential Equations) methods. We can compute these Monte Carlo samples for a quite large class of stochastic processes: any stochastic processes defined by an SDE (Stochastic Differential Equations), and also in high dimensions (we tested up to 64 dimensions). These samples can be used together with a PDE engine to boost convergence rate of regulatory type computations, as illustrated in the post.
Note that we used this sampling method for this Wilmot post.