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Daniel Dold
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2020 – today
- 2024
- [c3]Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr:
Bayesian Semi-structured Subspace Inference. AISTATS 2024: 1819-1827 - [i4]Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr:
Bayesian Semi-structured Subspace Inference. CoRR abs/2401.12950 (2024) - [i3]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 abs/2405.05429 (2024) - 2023
- [c2]Patrick Hoher, Johannes Reuter, Daniel Dold, Dennis Grießer, Felix Govaers, Wolfgang Koch:
Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model. FUSION 2023: 1-8 - 2022
- [c1]Matthias Hermann, Dennis Grießer, Bernhard Gundel, Daniel Dold, Georg Umlauf, Matthias O. Franz:
Targetless Lidar-camera registration using patch-wise mutual information. FUSION 2022: 1-8 - [i2]Oliver Dürr, Stephan Hörling, Daniel Dold, Ivonne Kovylov, Beate Sick:
Bernstein Flows for Flexible Posteriors in Variational Bayes. CoRR abs/2202.05650 (2022) - 2021
- [i1]Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick:
Transformation Models for Flexible Posteriors in Variational Bayes. CoRR abs/2106.00528 (2021)
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