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    Chapter and Conference Paper

    A General Machine Learning Framework for Survival Analysis

    The modeling of time-to-event data, also known as survival analysis, requires specialized methods that can deal with censoring and truncation, time-varying features and effects, and that extend to settings wit...

    Andreas Bender, David Rügamer in Machine Learning and Knowledge Discovery i… (2021)

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    Chapter and Conference Paper

    Deep Conditional Transformation Models

    Learning the cumulative distribution function (CDF) of an outcome variable conditional on a set of features remains challenging, especially in high-dimensional settings. Conditional transformation models provi...

    Philipp F. M. Baumann, Torsten Hothorn in Machine Learning and Knowledge Discovery i… (2021)