Issue
In some cases, once trained the predicted mean and covariance will be differentiable. Having a differentiable regressor can be useful in situations where the regressor is used for optimization or sampling etc. How can we enable this functionality
Possible solutions
As the RFs are simple objects, akin to neural networks, the ForwardDiff.jl/Zygote.jl packages for forward/backward differentiation may be used to differentiate the output, and are expected to work almost out-of-the box. We could investigate this
Issue
In some cases, once trained the predicted mean and covariance will be differentiable. Having a differentiable regressor can be useful in situations where the regressor is used for optimization or sampling etc. How can we enable this functionality
Possible solutions
As the RFs are simple objects, akin to neural networks, the ForwardDiff.jl/Zygote.jl packages for forward/backward differentiation may be used to differentiate the output, and are expected to work almost out-of-the box. We could investigate this