Andreas Bender

Orcid: 0000-0001-5628-8611

Affiliations:
  • LMU München, Department of Statistics, Munich, Germany (PhD 2018)


According to our database1, Andreas Bender authored at least 17 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Deep learning for survival analysis: a review.
Artif. Intell. Rev., March, 2024

A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data.
CoRR, 2024

Training Survival Models using Scoring Rules.
CoRR, 2024

2023
Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany.
J. Comput. Graph. Stat., 2023

Evaluating machine learning models in non-standard settings: An overview and new findings.
CoRR, 2023

Deep Learning for Survival Analysis: A Review.
CoRR, 2023

2022
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.
Bioinform., 2022

Factorized Structured Regression for Large-Scale Varying Coefficient Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021
Evaluation of survival distribution predictions with discrimination measures.
CoRR, 2021

Mundus vult decipi, ergo decipiatur: Visual Communication of Uncertainty in Election Polls.
CoRR, 2021

mlr3proba: an R package for machine learning in survival analysis.
Bioinform., 2021

Semi-Structured Deep Piecewise Exponential Models.
Proceedings of AAAI Symposium on Survival Prediction, 2021

2020
mlr3proba: Machine Learning Survival Analysis in R.
CoRR, 2020

A General Machine Learning Framework for Survival Analysis.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

2018
coalitions: Coalition probabilities in multi-party democracies.
J. Open Source Softw., 2018

2012
Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations.
Briefings Bioinform., 2012


  Loading...