Metadata-Version: 2.4
Name: bayesgm
Version: 1.0.0
Summary: A toolkit for AI-driven Bayesian Generative Modeling
Home-page: https://github.com/liuq-lab/bayesgm
Author: Qiao Liu
Author-email: qiao.liu@yale.edu
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7, <3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy==1.24.2
Requires-Dist: tensorflow==2.10.0
Requires-Dist: tensorflow-probability==0.18.0
Requires-Dist: pyyaml
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: tqdm
Requires-Dist: python-dateutil
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bayesgm is a toolkit providing a AI-driven Bayesian generative modeling framework for various Bayesian inference tasks in complex, high-dimensional data. The framework is built upon Bayesian principles combined with modern AI models, enabling flexible modeling of complex dependencies with principled uncertainty estimation. Currently, the bayesgm package includes two model families: BGM and CausalBGM.
