David Rügamer
Orcid: 0000-0002-8772-9202
According to our database1,
David Rügamer
authored at least 65 papers
between 2018 and 2024.
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Bibliography
2024
Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models.
Stat. Comput., February, 2024
Fusing structure from motion and simulation-augmented pose regression from optical flow for challenging indoor environments.
J. Vis. Commun. Image Represent., 2024
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects.
CoRR, 2024
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.
CoRR, 2024
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition.
CoRR, 2024
Proceedings of the Explainable Artificial Intelligence, 2024
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Team MGTD4ADL at SemEval-2024 Task 8: Leveraging (Sentence) Transformer Models with Contrastive Learning for Identifying Machine-Generated Text.
Proceedings of the 18th International Workshop on Semantic Evaluation, 2024
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract).
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Stat. Comput., April, 2023
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization.
J. Comput. Graph. Stat., April, 2023
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
J. Stat. Softw., 2023
Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany.
J. Comput. Graph. Stat., 2023
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models.
CoRR, 2023
Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization.
CoRR, 2023
Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition.
IEEE Access, 2023
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens.
Int. J. Document Anal. Recognit., 2022
Comput. Stat. Data Anal., 2022
CoRR, 2022
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression.
CoRR, 2022
Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022
Uncertainty-aware Evaluation of Time-series Classification for Online Handwriting Recognition with Domain Shift.
Proceedings of the 1st International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2022) co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI 2022, 2022
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition.
Proceedings of the Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges, 2022
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
2021
J. Stat. Softw., 2021
Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach.
CoRR, 2021
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation.
CoRR, 2021
CoRR, 2021
CoRR, 2021
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
CoRR, 2021
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
CoRR, 2021
Proceedings of AAAI Symposium on Survival Prediction, 2021
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021
2020
CoRR, 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020
2018