Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tractable Jacobian.
Hello, this is a great job
There is a problem, in the experiment Conditioner=DAG, Normalizer=Monotonic
How to calculate the inverse transformation of Graphical Normalizing Flow?
That is, how to get the generated data X' from the random noise Z by using the inverse transform X = g^-1(Z).
If this part of the code has been published, please tell me where it is, thank you