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Can we use compound distributions to represent Bayesian networks?
Some possible SymPy extensions:
- Support multiple compounded hyperparameters on one random symbol.
- Support nesting compound …
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File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/variational_inference/bayesian_neural_network_advi.ipynb
Reviewers:
> The sections below may still be pending. If so, the issue is …
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Port current example into colab. Add text from
+ http://edwardlib.org/tutorials/bayesian-neural-network
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I'm comparing different libraries for Bayesian inference and I'm wondering if my pomegranate tests show "correct" numbers or maybe I'm using it wrong. (Bit related to this closed issue: #811 )
My 2…
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### Subject of the issue
Add support for causal inference in Bayesian Networks. It should be a new class accepting all the models on which causal inference can be done (Bayesian Networks and SEM at t…
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Hello,
In version 0.14.8, it was possible to learn a Bayesian Network structure from sample data using the `from_samples` method. However, in version 1.0.4, I am unable to access this method from t…
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I think that Bayesian neural networks would be a natural successor to our tutorials on Bayesian GLMs.
As far as the neural network library to use, I think [Flux](https://github.com/FluxML/Flux.jl) …
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I want to build a disease prediction model with Bayesian network using edward.
But I can't find a example or tutorial. Can you help me?
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Has the Mocapy++ been integrated into biopython. I can't seem to find any sample code on DBNs in biopython. Any help is appreciated. [I am specifically looking at parameter learning in DBNs]