David Rügamer

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 80

Top Topics

Online Handwriting

Chest Radiographs

Top Venues

J. Comput. Graph. Stat.

Publications

Philipp Kopper, David Rügamer, Raphael Sonabend, Bernd Bischl, Andreas Bender
Training Survival Models using Scoring Rules. CoRR (2024)
Anton Frederik Thielmann, Arik Reuter, Thomas Kneib, David Rügamer, Benjamin Säfken
Interpretable Additive Tabular Transformer Networks. Trans. Mach. Learn. Res. 2024 (2024)
Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? CoRR (2024)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction. WACV (2024)
David Rügamer, Chris Kolb, Tobias Weber, Lucas Kook, Thomas Nagler
Generalizing Orthogonalization for Models with Non-Linearities. CoRR (2024)
Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
Bayesian Semi-structured Subspace Inference. AISTATS (2024)
David Rügamer
Scalable Higher-Order Tensor Product Spline Models. AISTATS (2024)
David Rundel, Julius Kobialka, Constantin von Crailsheim, Matthias Feurer, Thomas Nagler, David Rügamer
Interpretable Machine Learning for TabPFN. CoRR (2024)
Daniel Schalk, Bernd Bischl, David Rügamer
Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models. Stat. Comput. 34 (1) (2024)
Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
Bayesian Semi-structured Subspace Inference. CoRR (2024)
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR (2024)
Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. CoRR (2024)
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR (2024)
Tobias Weber, Jakob Dexl, David Rügamer, Michael Ingrisch
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition. CoRR (2024)
David Rügamer
Scalable Higher-Order Tensor Product Spline Models. CoRR (2024)
David Köhler, David Rügamer, Matthias Schmid
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects. CoRR (2024)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis. PAKDD (3) (2023)
David Rügamer
A New PHO-rmula for Improved Performance of Semi-Structured Networks. CoRR (2023)
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
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. 105 (2) (2023)
David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
Probabilistic time series forecasts with autoregressive transformation models. Stat. Comput. 33 (2) (2023)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis. CoRR (2023)
Chris Kolb, Christian L. Müller, Bernd Bischl, David Rügamer
Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization. CoRR (2023)
Daniel Schalk, Bernd Bischl, David Rügamer
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization. J. Comput. Graph. Stat. 32 (2) (2023)
Zheyu Zhang, Han Yang, Bolei Ma, David Rügamer, Ercong Nie
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models. CoRR (2023)
Tobias Pielok, Bernd Bischl, David Rügamer
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent. ICLR (2023)
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. ECML/PKDD (1) (2023)
Felix Ott, Lucas Heublein, David Rügamer, Bernd Bischl, Christopher Mutschler
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments. CoRR (2023)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Unreading Race: Purging Protected Features from Chest X-ray Embeddings. CoRR (2023)
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. CoRR (2023)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition. IEEE Access 11 (2023)
Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Rügamer
Frequentist Uncertainty Quantification in Semi-Structured Neural Networks. AISTATS (2023)
David Rügamer
A New PHO-rmula for Improved Performance of Semi-Structured Networks. ICML (2023)
Cornelius Fritz, Giacomo De Nicola, Felix Günther, David Rügamer, Martje Rave, Marc Schneble, Andreas Bender, Maximilian Weigert, Ralph Brinks, Annika Hoyer, Ursula Berger, Helmut Küchenhoff, Göran Kauermann
Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany. J. Comput. Graph. Stat. 32 (3) (2023)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition. CoRR (2023)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction. CoRR (2023)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift. CoRR (2022)
Felix Ott, Nisha Lakshmana Raichur, David Rügamer, Tobias Feigl, Heiko Neumann, Bernd Bischl, Christopher Mutschler
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression. CoRR (2022)
Daniel Schalk, Bernd Bischl, David Rügamer
Privacy-Preserving and Lossless Distributed Estimation of High-Dimensional Generalized Additive Mixed Models. CoRR (2022)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach. WACV (2022)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. Teaching ML (2022)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition. ICPR Workshops (1) (2022)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Cross-Modal Common Representation Learning with Triplet Loss Functions. CoRR (2022)
David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl
Factorized Structured Regression for Large-Scale Varying Coefficient Models. ECML/PKDD (5) (2022)
David Rügamer, Philipp F. M. Baumann, Sonja Greven
Selective inference for additive and linear mixed models. Comput. Stat. Data Anal. 167 (2022)
Philipp Kopper, Simon Wiegrebe, Bernd Bischl, Andreas Bender, David Rügamer
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis. CoRR (2022)
Felix Ott, David Rügamer, Lucas Heublein, Tim Hamann, Jens Barth, Bernd Bischl, Christopher Mutschler
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens. CoRR (2022)
Patrick Kaiser, Christoph Kern, David Rügamer
Uncertainty-aware predictive modeling for fair data-driven decisions. CoRR (2022)
David Rügamer
Additive Higher-Order Factorization Machines. CoRR (2022)
Andreas Klaß, Sven M. Lorenz, Martin W. Lauer-Schmaltz, David Rügamer, Bernd Bischl, Christopher Mutschler, Felix Ott
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift. CoRR (2022)
Felix Ott, David Rügamer, Lucas Heublein, Tim Hamann, Jens Barth, Bernd Bischl, Christopher Mutschler
Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens. Int. J. Document Anal. Recognit. 25 (4) (2022)
Philipp Schiele, Christoph Berninger, David Rügamer
ARMA Cell: A Modular and Effective Approach for Neural Autoregressive Modeling. CoRR (2022)
Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl
Joint Debiased Representation Learning and Imbalanced Data Clustering. ICDM (Workshops) (2022)
Philipp Kopper, Simon Wiegrebe, Bernd Bischl, Andreas Bender, David Rügamer
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis. PAKDD (2) (2022)
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift. ACM Multimedia (2022)
David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl
Factorized Structured Regression for Large-Scale Varying Coefficient Models. CoRR (2022)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs. MAD@MICCAI (2022)
Andreas Klaß, Sven M. Lorenz, Martin W. Lauer-Schmaltz, David Rügamer, Bernd Bischl, Christopher Mutschler, Felix Ott
Uncertainty-aware Evaluation of Time-series Classification for Online Handwriting Recognition with Domain Shift. STRL@IJCAI (2022)
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
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. CoRR (2021)
David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
Transforming Autoregression: Interpretable and Expressive Time Series Forecast. CoRR (2021)
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
Deep Conditional Transformation Models. ECML/PKDD (3) (2021)
Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl
Deep Semi-supervised Learning for Time Series Classification. ICMLA (2021)
Stefan Coors, Daniel Schalk, Bernd Bischl, David Rügamer
Automatic Componentwise Boosting: An Interpretable AutoML System. CoRR (2021)
Benjamin Säfken, David Rügamer, Thomas Kneib, Sonja Greven
Conditional Model Selection in Mixed-Effects Models with cAIC4. J. Stat. Softw. 99 (8) (2021)
Magdalena Mittermeier, Maximilian Weigert, David Rügamer
Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach. CoRR (2021)
Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl
Deep Semi-Supervised Learning for Time Series Classification. CoRR (2021)
Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation. CoRR (2021)
Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David Rügamer
Semi-Structured Deep Piecewise Exponential Models. SPACA (2021)
Daniel Schalk, Bernd Bischl, David Rügamer
Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization. CoRR (2021)
Cornelius Fritz, Emilio Dorigatti, David Rügamer
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany. CoRR (2021)
Tobias Weber, Michael Ingrisch, Matthias Fabritius, Bernd Bischl, David Rügamer
Survival-oriented embeddings for improving accessibility to complex data structures. CoRR (2021)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. CoRR (2021)
Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl
Learning Statistical Representation with Joint Deep Embedded Clustering. CoRR (2021)
Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David Rügamer
Semi-Structured Deep Piecewise Exponential Models. CoRR (2020)
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl
A General Machine Learning Framework for Survival Analysis. CoRR (2020)
David Rügamer, Sonja Greven
-Boosting. Stat. Comput. 30 (2) (2020)
David Rügamer, Florian Pfisterer, Bernd Bischl
Neural Mixture Distributional Regression. CoRR (2020)
David Rügamer, Chris Kolb, Nadja Klein
A Unifying Network Architecture for Semi-Structured Deep Distributional Learning. CoRR (2020)
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl
A General Machine Learning Framework for Survival Analysis. ECML/PKDD (3) (2020)
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
Deep Conditional Transformation Models. CoRR (2020)
David Rügamer, Sonja Greven
-Boosting. CoRR (2018)