Backward filtering-forward guiding algorithm

Backward filtering-forward guiding algorithm is a computational framework for sampling conditioned diffusions, it has been described in detail in this paper and it is what happens behind the scenes of GuidedProposals.jl.

Briefly, it comprises of two passes, that—if repeated many times—may result in a smoothing or inference algorithms. The two steps are:

• backward filtering &
• forward guiding.

Backward filtering

Backward filtering is a technical term for propagating the information about the observations (that lie in the future) back into the parts of the interval that precede them (and on which the diffusion is defined). It is simply the process of computing the guiding term. It is done implicitly every time GuidProp is instantiated. Additionally, after parameters change it may also be done explicitly by calling recompute_guiding_term! or its alias

see the section on reparameterizations for more details.

Forward guiding

Forward guiding is a technical term for sampling guiding proposals. It is encapsulated by various rand, rand! and solve_and_ll! routines. You may also call

See sections Defining guided proposals and Guided proposals with multiple observations for more details about sampling.