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py-why / dowhy

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DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

data-science machine-learning python3 graphical-models causality bayesian-networks causal-inference treatment-effects causal-models do-calculus causal-machine-learning
  • Updated May 28, 2024
  • Python

kumar-shridhar / PyTorch-BayesianCNN

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Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

python pytorch bayesian-network image-recognition convolutional-neural-networks bayesian-inference bayes bayesian-networks variational-inference bayesian-statistics bayesian-neural-networks variational-bayes bayesian-deep-learning pytorch-cnn bayesian-convnets bayes-by-backprop aleatoric-uncertainties
  • Updated Apr 19, 2024
  • Python

ax-va / Project-BayesianPy

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This is a collection of algorithms and models written in Python for probabilistic programming. The main focus of the package is on Bayesian reasoning by using Bayesian networks, Markov networks, and their mixing.

machine-learning machine-learning-algorithms pgm inference bayesian-network probabilistic-programming bayesian-inference bayesian-networks probabilistic-graphical-models bayesian-machine-learning markov-networks probabilistic-reasoning markov-network bayesian-reasoning
  • Updated Apr 29, 2023
  • Python

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