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Rudolph Triebel
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Publications
- 2023
- [c97]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. ICML 2023: 30252-30284 - [i36]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. CoRR abs/2307.07753 (2023) - 2021
- [c69]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. IROS 2021: 8737-8744 - [i24]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. CoRR abs/2109.05509 (2021) - 2020
- [c54]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. ECML/PKDD (2) 2020: 85-100 - [i11]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. CoRR abs/2006.12456 (2020) - 2018
- [c48]Ioannis Chiotellis, Franziska Zimmermann, Daniel Cremers, Rudolph Triebel:
Incremental Semi-Supervised Learning from Streams for Object Classification. IROS 2018: 5743-5749 - 2016
- [c40]Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, Daniel Cremers:
Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding. ECCV (2) 2016: 327-342 - [c39]Alexander Narr, Rudolph Triebel, Daniel Cremers:
Stream-based Active Learning for efficient and adaptive classification of 3D objects. ICRA 2016: 227-233 - [i1]Sahand Sharifzadeh, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks. CoRR abs/1612.03653 (2016) - 2015
- [c38]Rudolph Triebel, Kai Oliver Arras, Rachid Alami, Lucas Beyer, Stefan Breuers, Raja Chatila, Mohamed Chetouani, Daniel Cremers, Vanessa Evers, Michelangelo Fiore, Hayley Hung, Omar A. Islas Ramírez, Michiel Joosse, Harmish Khambhaita, Tomasz Kucner, Bastian Leibe, Achim J. Lilienthal, Timm Linder, Manja Lohse, Martin Magnusson, Billy Okal, Luigi Palmieri, Umer Rafi, Marieke van Rooij, Lu Zhang:
SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports. FSR 2015: 607-622 - [c37]Dennis Mund, Rudolph Triebel, Daniel Cremers:
Active online confidence boosting for efficient object classification. ICRA 2015: 1367-1373 - [c36]Ye Tao, Rudolph Triebel, Daniel Cremers:
Semi-supervised online learning for efficient classification of objects in 3D data streams. IROS 2015: 2904-2910 - 2014
- [c35]Thomas Windheuser, Matthias Vestner, Emanuele Rodolà, Rudolph Triebel, Daniel Cremers:
Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis. BMVC 2014 - [c34]Rudolph Triebel, Jan Stühmer, Mohamed Souiai, Daniel Cremers:
Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes. GCPR 2014: 641-652 - [c33]Shoubhik Debnath, Shiv Sankar Baishya, Rudolph Triebel, Varun Dutt, Daniel Cremers:
Environment-Adaptive Learning: How Clustering Helps to Obtain Good Training Data. KI 2014: 68-79
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