Comments (2)
Hi Prof. @cranmer,
there existed some support for flows conditioned on continuous variables scattered around the package, but it was incomplete and, indeed, not very well documented.
I added some functionality now, such as a ConditionalNormalizingFlow
model class, a ConditionalDiagGaussian
base distribution, where the parameters are encoded by the conditional, and a few flows support now conditional variables. An example for a conditional MAF and a conditional autoregressive NSF is given here; it is also in the documentation.
If there is any particular flow besides those implemented that you want to use with continuous conditional variables, please let me know.
Best regards,
Vincent
PS: Note that these additions are currently only available on the GitHub, but I will update the release on PyPI soon.
from normalizing-flows.
The changes are part of the new version of the package I just released on PyPI. Hence, I'll close this issue. If there are still more features you wish to be included, please create a new issue.
from normalizing-flows.
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from normalizing-flows.