Closed rminhas closed 4 years ago
Yup, thank you for the report. We are looking into how the adjoint can be extended to allow mass matrices. It doesn't seem to be that difficult, so I think we may have it sooner rather than later.
Great - thanks.
Hi there @ChrisRackauckas, any update on this? I have a problem where I'd like to either have a DAE solve as part of the loss function, or as the last layer of the network (either would work for my application) – is there any way to do that right now?
Thanks for this package, it was the thing that finally pushed me to bite the bullet and learn Julia. :)
There's an implementation here https://github.com/JuliaDiffEq/DiffEqSensitivity.jl/pull/86 and it works with non-singular mass matrices, but I can't find out why it doesn't work for singular mass matrices.
Non-singular mass matrices are now supported, but singular mass matrices are coming next.
It's good now.
I'm trying to use a DAE as a layer in a neural net. When the DAE is specified as an
ODEProblem
using anODEFunction
andmass_matrix
, DiffEqFlux cansolve
the problem but it cannot be used in a neural net usingdiffeq_adjoint
. On the Slack channel, @ChrisRackauckas mentioned that mass matrices are currently not compatible withdiffeq_adjoint
. I'm reporting this issue here so it can be tracked. Thanks.