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For my thesis, I need to use DAGs/SCMs. This is in continuation of my previous bug raised: https://github.com/py-why/dowhy/issues/1241
If I have a GCM, how can I achieve the following:
1. When I…
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I created a BayesianNetwork and fit the data:
`model = BayesianNetwork(algorithm="chow-liu", max_parents=max_parents)`
`model.fit(data)`
In `fit` method, it calls `_learn_structure` method, ho…
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Hi there,
I'm actively developing and maintaining a package on Bayesian nonparametrics in julia:
[BayesianNonparametrics.jl](https://github.com/OFAI/BayesianNonparametrics.jl)
which was presente…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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This issue can be a collection and discussion of methods we could add to the library at some point, in no particular order :) Feel free to comment with suggestions and if you feel comfortable, you are…
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Hi,
I am trying to use tensorflow probability to learn a Bayesian neural networks. I want to learn the responses y_t based on input features x_t, i.e.
` y_t = f(x_t) + eps`
where f(x_t) is th…
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The paper "Likelihood-free parameter estimation with neural Bayes estimators" (Sainsbury-Dale, Zammit-Mangion, & Huser, 2023) enables neural amortized *point* estimation, which is generally faster tha…
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**Summary !!!**
- **BioModel Name**: Beker2020 - Drug-likeness prediction based on Bayesian neural networks
- **BioModel Tag**: Machine learning model, Ersilia, FAIR AIML
- **Metadata Comment…
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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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## 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…