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    Chapter and Conference Paper

    DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis

    Survival analysis (SA) is an active field of research that is concerned with time-to-event outcomes and is prevalent in many domains, particularly biomedical applications. Despite its importance, SA remains ch...

    Philipp Kopper, Simon Wiegrebe, Bernd Bischl in Advances in Knowledge Discovery and Data M… (2022)

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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)