Abstract
The authors present an ingenious probabilistic numerical solver for deterministic differential equations (DEs). The true solution is progressively identified via model interrogations, in a formal framework of Bayesian updating. I have attempted to extend the authors’ ideas to stochastic differential equations (SDEs), and discuss two challenges encountered in this endeavor: (i) the non-differentiability of SDE sample paths, and (ii) the sampling of diffusion bridges, typically required of solutions to the SDE inverse problem.
Citation
Martin Lysy. "Comment on Article by Chkrebtii, Campbell, Calderhead, and Girolami." Bayesian Anal. 11 (4) 1269 - 1273, December 2016. https://doi.org/10.1214/16-BA1036
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