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### Subject of the issue
How to entering soft (uncertain evidence) in discrete Bayesian networks?
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Terminology definition:
Hard evidence: if we are 100% sure (this is observation True)
Soft …
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### Subject of the issue
Hi there, I have a silly question about the scalability of pgmpy. I am planning to construct a Bayesian Network with 360 features, each feature can have around 1000 states. T…
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Hello, I am trying to use this repository for regression tasks (I can see the examples seem to focus on classification tasks).
I would like to do estimate epistemic and aleatoric uncertainty for m…
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I have read the following issue posts: https://github.com/tensorflow/probability/issues/325 and https://github.com/tensorflow/probability/issues/289.
I know I can just save/load the weights of a BN…
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## Work to Replicate
Gal, Y., McAllister, R. and Rasmussen, C.E., 2016, April. Improving PILCO with Bayesian neural network dynamics models. In Data-Efficient Machine Learning workshop, ICML.
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not sure how ABC fits in but it would be helpful for me to write down a network diagram and associated equations for the model that I can update as we make changes (work with Jude on this)
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### Issue Type
Bug
### Source
binary
### Keras Version
2.16.0
### Custom Code
No
### OS Platform and Distribution
Linux Ubuntu 20.04
### Python version
3.10
### GPU model and memory
_No r…
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## 一言でいうと
予測の不確実性を推定する手法の提案。既存研究ではDropoutを使った不確実推定があったが、Dropoutよりもよく使われているBatch Normalizationを使い推定する。正規化に用いる平均/分散を学習データからサンプリングすることでモデル出力の分布を得る。
![image](https://user-images.githubusercontent.co…
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Search for "mixed variable bayesian network" models. or "hybrid bayesian networks"
E.g.,
https://par.nsf.gov/servlets/purl/10048513
Conditional Gaussian seems to be a popular choice.
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- [x] Figure out how (or if) they sample variance of ensemble of networks.