You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Currently, the gradients of the transformation function are numerically approximated. Providing an option to pass a gradient function may speed up the computation. The main drawback is that users would have to implement a jacobian matrix because the transformation function takes a vector as input and returns a vector.
For the time being I will leave this issue open until there is a practical use case where numerical approximations are too slow.
The text was updated successfully, but these errors were encountered:
Currently, the gradients of the transformation function are numerically approximated. Providing an option to pass a gradient function may speed up the computation. The main drawback is that users would have to implement a jacobian matrix because the transformation function takes a vector as input and returns a vector.
For the time being I will leave this issue open until there is a practical use case where numerical approximations are too slow.
The text was updated successfully, but these errors were encountered: