output
20202025
most citedDeep Learning for Survival Analysis: A Review

170 citations

5 papers

stat.ML2025

Reduction Techniques for Survival Analysis

Johannes Piller, Léa Orsini, Simon Wiegrebe +6

In this work, we discuss what we refer to as reduction techniques for survival analysis, that is, techniques that "reduce" a survival task to a more common regression or classifica…

stat.AP2024

Which Imputation Fits Which Feature Selection Method? A Survey-Based Simulation Study

Jakob Schwerter, Andrés Romero, Florian Dumpert +1

Tree-based learning methods such as Random Forest and XGBoost are still the gold-standard prediction methods for tabular data. Feature importance measures are usually considered fo…

stat.ML2023★ 170 cited

Deep Learning for Survival Analysis: A Review

Simon Wiegrebe, Philipp Kopper, Raphael Sonabend +2

The influx of deep learning (DL) techniques into the field of survival analysis in recent years has led to substantial methodological progress; for instance, learning from unstruct…

stat.ME2020

Data Fusion for Joining Income and Consumption Information Using Different Donor-Recipient Distance Metrics

Florian Meinfelder, Jannik Schaller

Data fusion describes the method of combining data from (at least) two initially independent data sources to allow for joint analysis of variables which are not jointly observed. T…

cs.CV2020★ 6 cited

Monitoring Spatial Sustainable Development: semi-automated analysis of Satellite and Aerial Images for Energy Transition and Sustainability Indicators

Tim De Jong, Stefano Bromuri, Xi Chang +6

This report presents the results of the DeepSolaris project that was carried out under the ESS action 'Merging Geostatistics and Geospatial Information in Member States'. During th…