Thanks, I’m indeed interested in using their BFFG algorithm later in my work.
I was able to take advantage of the fact that an OU bridge have the following general-linear SDE representation from Barczy & Kern (2013)
and solve the problem by defining a custom drift function.
Then general idea I wanted to accomplish however was
w_noise = WienerProcess(...)
oub_noise= DiffEqNoiseProcess.OrnsteinUhlenbeckBridge(...)
W = [w_noise, oub_noise]
prob = SDEProblem(drift!, diffusion!, u0, (0.0, Δt), noise = W)
where the drift function would output a vector for a diagonal noise process.
Seems like it may be possible by defining a custom NoiseProcess but I came across the reference while trying to understand the custom constructor.
Apologies for the lack of clarity in my previous posts.