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


Apr 06, 2021
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


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Deep Semi-Supervised Learning for Time Series Classification


Feb 06, 2021
Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl


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Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany


Jan 03, 2021
Cornelius Fritz, Emilio Dorigatti, David Rügamer


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Semi-Structured Deep Piecewise Exponential Models


Nov 11, 2020
Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David Rügamer

* 8 pages, 3 figures 

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Deep Conditional Transformation Models


Oct 15, 2020
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer


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Neural Mixture Distributional Regression


Oct 14, 2020
David Rügamer, Florian Pfisterer, Bernd Bischl


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A General Machine Learning Framework for Survival Analysis


Jun 27, 2020
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl

* Accepted at ECML PKDD 2020, Research Track 

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A Unifying Network Architecture for Semi-Structured Deep Distributional Learning


Feb 13, 2020
David Rügamer, Chris Kolb, Nadja Klein


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Selective Inference for $L_2$-Boosting


Oct 29, 2018
David Rügamer, Sonja Greven


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Boosting Factor-Specific Functional Historical Models for the Detection of Synchronisation in Bioelectrical Signals


May 13, 2017
David Rügamer, Sarah Brockhaus, Kornelia Gentsch, Klaus Scherer, Sonja Greven

* Revised version 

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