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@SamWitty linked this repo https://github.com/SciML/diffeqpy which also allows for SDEs. It might be faster than torchdiffeq too. We would need to wrap it so that Torch can access the gradients.
The text was updated successfully, but these errors were encountered:
There's also this issue that mentions that this other package called torchdyn was thinking about using DifferentialEquations.jl as a backend: SciML/diffeqpy#67
@SamWitty linked this repo https://github.com/SciML/diffeqpy which also allows for SDEs. It might be faster than torchdiffeq too. We would need to wrap it so that Torch can access the gradients.
The text was updated successfully, but these errors were encountered: