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10/16/2020
Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes
Outcomes with a natural order commonly occur in prediction tasks and oft...
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10/15/2020
Deep Conditional Transformation Models
Learning the cumulative distribution function (CDF) of an outcome variab...
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04/01/2020
Deep transformation models: Tackling complex regression problems with neural network based transformation models
We present a deep transformation model for probabilistic regression. Dee...
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01/02/2020
Circular Regression Trees and Forests with an Application to Probabilistic Wind Direction Forecasting
While circular data occur in a wide range of scientific fields, the meth...
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10/21/2019
Marginally Interpretable Linear Transformation Models for Clustered Observations
Clustered observations are ubiquitous in controlled and observational st...
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06/24/2019
The Power of Unbiased Recursive Partitioning: A Unifying View of CTree, MOB, and GUIDE
A core step of every algorithm for learning regression trees is the sele...
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06/07/2019
Multivariate Conditional Transformation Models
Regression models describing the joint distribution of multivariate resp...
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02/05/2019
Survival Forests under Test: Impact of the Proportional Hazards Assumption on Prognostic and Predictive Forests for ALS Survival
We investigate the effect of the proportional hazards assumption on prog...
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04/09/2018
Distributional Regression Forests for Probabilistic Precipitation Forecasting in Complex Terrain
To obtain a probabilistic model for a dependent variable based on some s...
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06/26/2017
Top-down Transformation Choice
Simple models are preferred over complex models, but over-simplistic mod...
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01/09/2017