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Title: GitHub - mlpapers/bayesian-nets: Awesome papers on Bayesian Networks

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Wikihttps://en.wikipedia.org/wiki/Bayesian_network
Introducing Bayesian Networkshttps://bayesian-intelligence.com/publications/bai/book/BAI_Chapter2.pdf
Bayesian Artificial Intelligencehttps://bayesian-intelligence.com/publications/bai/
A Tutorial on Learning With Bayesian Networkshttps://arxiv.org/pdf/2002.00269.pdf
https://patch-diff.githubusercontent.com/mlpapers/bayesian-nets#types
Learning Gaussian Networkshttps://arxiv.org/pdf/1302.6808.pdf
Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitativehttps://projecteuclid.org/euclid.aos/1176347003
Copula Bayesian Networkshttps://papers.nips.cc/paper/3956-copula-bayesian-networks.pdf
Dynamic Network Models for Forecastinghttp://erichorvitz.com/dynamic_network_models_UAI_1992.pdf
Dynamic Bayesian Networks: Representation, Inference and Learninghttps://www.cs.ubc.ca/~murphyk/Thesis/thesis.pdf
https://patch-diff.githubusercontent.com/mlpapers/bayesian-nets#structure-learning
Equivalence and Synthesis of Causal Modelshttps://arxiv.org/pdf/1304.1108.pdf
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithmhttps://arxiv.org/pdf/1301.6696.pdf
Optimal Structure Identification With Greedy Searchhttp://www.ai.mit.edu/projects/jmlr/papers/volume3/chickering02b/chickering02b.pdf
Learning Bayesian Networks with Thousands of Variableshttps://papers.nips.cc/paper/5803-learning-bayesian-networks-with-thousands-of-variables.pdf
Learning Bayesian networks from big data with greedy search:computational complexity and efficient implementationhttps://link.springer.com/content/pdf/10.1007%2Fs11222-019-09857-1.pdf
Learning Bayesian Network Model Structure from Datahttps://www.cs.cmu.edu/~dmarg/Papers/PhD-Thesis-Margaritis.pdf
Algorithms for Large Scale Markov Blanket Discoveryhttps://www.aaai.org/Papers/FLAIRS/2003/Flairs03-073.pdf
Speculative Markov BlanketDiscoveryforOptimalFeature Selectionhttp://www.cs.cmu.edu/~dmarg/Papers/Yaramakala-Margaritis-ICDM05.pdf
Optimal Reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learninghttps://web.engr.oregonstate.edu/~wongwe/papers/pdf/optreinsert.2003.pdf
The max-min hill-climbing Bayesian network structure learning algorithmhttps://link.springer.com/content/pdf/10.1007%2Fs10994-006-6889-7.pdf
Learning Bayesian Networks: The Combination of Knowledge and Statistical Datahttp://www.cs.technion.ac.il/~dang/journal_papers/heckerman1995learning.pdf
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