739 citations · 1.4k across the 25 of their papers we have counts for
27 papers
Deep conditional transformation models for survival analysis
Gabriele Campanella, Lucas Kook, Ida Häggström +2
An every increasing number of clinical trials features a time-to-event outcome and records non-tabular patient data, such as magnetic resonance imaging or text data in the form of…
Matching Text and Audio Embeddings: Exploring Transfer-learning Strategies for Language-based Audio Retrieval
Benno Weck, Miguel Pérez Fernández, Holger Kirchhoff +1
We present an analysis of large-scale pretrained deep learning models used for cross-modal (text-to-audio) retrieval. We use embeddings extracted by these models in a metric learni…
Transformation models for ROC analysis
Ainesh Sewak, Torsten Hothorn
Receiver operating characteristic (ROC) analysis is one of the most popular approaches for evaluating and comparing the accuracy of medical diagnostic tests. Although various metho…
Distribution-Free Location-Scale Regression
Sandra Siegfried, Lucas Kook, Torsten Hothorn
We introduce a generalized additive model for location, scale, and shape (GAMLSS) next of kin aiming at distribution-free and parsimonious regression modelling for arbitrary outcom…
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Susanne Dandl, Torsten Hothorn, Heidi Seibold +3
Estimation of heterogeneous treatment effects (HTE) is of prime importance in many disciplines, ranging from personalized medicine to economics among many others. Random forests ha…
Joint Count Transformation Models with Covariate-dependent Correlations
Lukas Graz, Luisa Barbanti, Roland Brandl +1
Joint Species Distribution Models are essential for understanding how ecological covariates shape species communities. However, most existing approaches are limited by rigid parame…