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WiseR: An end-to-end structure learning and deployment framework for causal graphical models

16 August 2021
Shubham Maheshwari
Khushbu Pahwa
Tavpritesh Sethi
    CML
ArXiv (abs)PDFHTML
Abstract

Structure learning offers an expressive, versatile and explainable approach to causal and mechanistic modeling of complex biological data. We present wiseR, an open source application for learning, evaluating and deploying robust causal graphical models using graph neural networks and Bayesian networks. We demonstrate the utility of this application through application on for biomarker discovery in a COVID-19 clinical dataset.

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