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A multivariate additive noise model for complete causal discovery

Neural Networks : the Official Journal of the International Neural Network Society

Jul 26, 2018

Pramod Kumar ParidaSnehashish Chakraverty

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Abstract

Explaining causal reasoning in the form of directed acyclic graphs (DAGs) yields nodal structures with multivariate relationships. In real-world phenomena, these effects can be seen as multiple feature dependency with unmeasured external influences or noises. The bivariate models for ca...read more

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  • A multivariate additive noise model for complete causal discovery

    Neural Networks : the Official Journal of the International Neural Network Society

    Jul 26, 2018

    Pramod Kumar ParidaSnehashish Chakraverty

    PMID: 29626732

    DOI: 10.1016/j.neunet.2018.03.013

    Abstract

    Explaining causal reasoning in the form of directed acyclic graphs (DAGs) yields nodal structures with multivariate relationships. In real-world phenomena, these effects can be seen as multiple feature dependency with unmeasured external influences or noises. The bivariate models for ca...read more

    1
    6
    21

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