Riccardo De Bin

Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex

Pascal Friederich, Gabriel dos Passos Gomes, Riccardo De Bin et al. · Chemical Science · 2020 · 183 citations · Full text

Subsampling Versus Bootstrapping in Resampling-Based Model Selection for Multivariable Regression

Riccardo De Bin, Silke Janitza, Willi Sauerbrei et al. · Biometrics · 2015 · 99 citations · Full text

IPF-LASSO: Integrative<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi>L</mml:mi></mml:mrow><mml:mrow><mml:mn fontstyle="italic">1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

Anne‐Laure Boulesteix, Riccardo De Bin, Xiaoyu Jiang et al. · Computational and Mathematical Methods in Medicine · 2017 · 91 citations · Full text

Standard Lasso, Machine Learning, Engineering +25

Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost

Riccardo De Bin · Computational Statistics · 2016 · 61 citations · Full text

Predictive Analytics, Model-based Approaches, Time-varying Confounding +6

Investigating the prediction ability of survival models based on both clinical and omics data: two case studies

Riccardo De Bin, Willi Sauerbrei, Anne‐Laure Boulesteix · Statistics in Medicine · 2014 · 50 citations · Full text