Lucas Kook

According to our database, Lucas Kook authored at least 8 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics.

Fernando Marmolejo-Ramos, Mauricio Tejo, Marek Brabec, Jakub Kuzilek, Srecko Joksimovic, Vitomir Kovanovic, Jorge González, Thomas Kneib, Peter Bühlmann, Lucas Kook, Guillermo Briseño-Sánchez, Raydonal Ospina

WIREs Data Mining Knowl. Discov., 2023

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.

David Rügamer, Chris Kolb, Cornelius Fritz, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Philipp F. M. Baumann, Lucas Kook, Nadja Klein, Christian L. Müller

J. Stat. Softw., 2023

2022

Distributional anchor regression.

Lucas Kook, Beate Sick, Peter Bühlmann

Stat. Comput., 2022

Deep and interpretable regression models for ordinal outcomes.

Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick

Pattern Recognit., 2022

Deep conditional transformation models for survival analysis.

Gabriele Campanella, Lucas Kook, Ida Häggström, Torsten Hothorn, Thomas J. Fuchs

CoRR, 2022

Deep interpretable ensembles.

Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick

CoRR, 2022

2021

Regularized Transformation Models: The tramnet Package.

Lucas Kook, Torsten Hothorn

R J., 2021

2020

Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes.

Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick

CoRR, 2020