Libraries for Bayesian network inference with continuous data

Is there any good libraries that allow me to:

1. Construct a Bayesian network manually
2. Specify the conditional probabilities with any continuous PDF, not just Guassian
3. Perform inference, either exact or approximate

I looked at the following libraries so far, none of them meet the 3 requirements:

• pgmpy: only work on discrete distribution or linear Guassian distribution
• bnlearn: same as pgmpy
• gRain: only discrete distribution
• Huggin: only discrete distribution and Guassian
• deal: no support for inference
• abn: same as deal
• libpgm: only discrete distribution and Guassian
• Investigate tensorflow, edward, and pymc – Emre Apr 12 '17 at 3:25

Not a library, but a interactive GUI based tool is "samiam" (Sensitivity Analysis Modeling Inference and More) from a research group at UCLA.

I am not sure about your "continuous PDFs" requirement, whether it's possible to define them inside the samiam GUI.

For API-access, you might call functions inside the inflib.jar file.