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Dear author,
I found there might be a bug in Bayesian network's sample function.
![image](https://github.com/jmschrei/pomegranate/assets/135833420/94ce886f-01cd-4820-a2d2-3d3dcfbd997b)
For the abov…
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**Submitting author:** @matteodelucchi (Matteo Delucchi)
**Repository:** https://github.com/furrer-lab/abn
**Branch with paper.md** (empty if default branch):
**Version:** 3.1.0
**Editor:** @crvernon…
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Hi, I hope to use a time series data to fit a dynamic bayesian network. But after looking up the docs, I didn't find dynamic bayesian network class.
I'm wondering is there any easy method to extent t…
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Thank you very much for your task, I have been following up your research recently, may I ask where is the code related to Bayesian networks? I didn't see the code for the Bayesian network model
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In the [Bayesian Neural Network ](https://turing.ml/dev/tutorials/03-bayesian-neural-network/) tutorial, there is code for a "Generic Bayesian Neural Network," that rebuilds the Flux model with the ne…
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### Subject of the issue
Excessive memory usage when using maximum likelihood estimation.
### Your environment
* pgmpy version: 0.1.25
* Python version: 3.12
* Operating System: windows10
##…
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Work with multi-layer bayesian neural networks and compare it with more classical methods (ADVI).
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I think we can do something really cool about converting deterministic code into Bayesian programs. From the data structures that we have we can put on every variable a distribution and then run the n…
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- Time 0 model (baseline conditions and time-dependent variables at T=1)
- Time t model (maps time-dependent variables at time t to the same at time t+1) • unroll.markovNetwork(startTime=NULL, stop…
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Hello,
I have been looking for a Julia package to perform amortized Bayesian inference on simulation-based models. In many areas of science, there are models with unknown/intractable likelihood fu…