Philipp Kopper

According to our database, Philipp Kopper authored at least 11 papers between 2021 and 2025.

Collaborative distances:

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

2025

mlr3extralearners: Expanding the mlr3 Ecosystem with Community-Driven Learner Integration.

Sebastian Fischer, John Zobolas, Raphael Sonabend, Marc Becker, Michel Lang, Martin Binder, Lennart Schneider, Lukas Burk, Patrick Schratz, Byron C. Jaeger, Stephen A. Lauer, Lorenz A. Kapsner, Maximilian Mücke, Zezhi Wang, Damir Pulatov, Keenan Ganz, Henri Funk, Liana Harutyunyan, Pierre Camilleri, Philipp Kopper, Andreas Bender, Baisu Zhou, Niko German, Lona Koers, Anna Nazarova, Bernd Bischl

J. Open Source Softw., December, 2025

mlr3extralearners: Expanding the mlr3 Ecosystem with Community-Driven Learner Integration.

Sebastian Fischer, John Zobolas, Raphael Sonabend, Marc Becker, Michel Lang, Martin Binder, Lennart Schneider, Lukas Burk, Patrick Schratz, Byron C. Jaeger, Stephen A. Lauer, Lorenz A. Kapsner, Maximilian Mücke, Zezhi Wang, Damir Pulatov, Keenan Ganz, Henri Funk, Liana Harutyunyan, Pierre Camilleri, Philipp Kopper, Andreas Bender, Baisu Zhou, Niko German, Lona Koers, Anna Nazarova, Bernd Bischl

Dataset, November, 2025

On Training Survival Models with Scoring Rules.

Philipp Kopper, David Rügamer, Raphael Sonabend, Bernd Bischl, Andreas Bender

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

2024

Deep learning for survival analysis: a review.

Simon Wiegrebe, Philipp Kopper, Raphael Sonabend, Bernd Bischl, Andreas Bender

Artif. Intell. Rev., March, 2024

Training Survival Models using Scoring Rules.

Philipp Kopper, David Rügamer, Raphael Sonabend, Bernd Bischl, Andreas Bender

CoRR, 2024

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.

Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer

Proceedings of the Uncertainty in Artificial Intelligence, 2024

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

Deep Learning for Survival Analysis: A Review.

Simon Wiegrebe, Philipp Kopper, Raphael Sonabend, Andreas Bender

CoRR, 2023

2022

DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.

Philipp Kopper, Simon Wiegrebe, Bernd Bischl, Andreas Bender, David Rügamer

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021

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

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

CoRR, 2021

Semi-Structured Deep Piecewise Exponential Models.

Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David Rügamer

Proceedings of AAAI Symposium on Survival Prediction, 2021