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ORCIDGabriel Kalweit
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2020 – today
- 2022
[b1]Gabriel Kalweit:
On the role of time horizons in reinforcement learning. University of Freiburg, Freiburg im Breisgau, Germany, 2022- [c10]Maria Kalweit, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Deep Surrogate Q-Learning for Autonomous Driving. ICRA 2022: 1578-1584 - [c9]Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard:
Affordance Learning from Play for Sample-Efficient Policy Learning. ICRA 2022: 6372-6378 - [i11]Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard:
Affordance Learning from Play for Sample-Efficient Policy Learning. CoRR abs/2203.00352 (2022) - [i10]Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard:
Latent Plans for Task-Agnostic Offline Reinforcement Learning. CoRR abs/2209.08959 (2022) - 2021
- [c8]Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. ICRA 2021: 1028-1035 - [c7]Maria Kalweit, Gabriel Kalweit, Joschka Boedecker:
AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. AI4Function@IJCAI 2021: 12-21 - [c6]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. IROS 2021: 5641-5648 - 2020
- [c5]Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard:
Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. ICRA 2020: 4188-4194 - [c4]Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker
:
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. ICRA 2020: 4329-4335 - [c3]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Deep Inverse Q-learning with Constraints. NeurIPS 2020 - [i9]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving. CoRR abs/2003.09398 (2020) - [i8]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Deep Inverse Q-learning with Constraints. CoRR abs/2008.01712 (2020) - [i7]Maria Hügle, Gabriel Kalweit, Thomas Huegle, Joschka Boedecker:
A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. CoRR abs/2008.06294 (2020) - [i6]Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Deep Surrogate Q-Learning for Autonomous Driving. CoRR abs/2010.11278 (2020) - [i5]Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. CoRR abs/2012.03234 (2020)
2010 – 2019
- 2019
- [c2]Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker:
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. IROS 2019: 7566-7573 - [i4]Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker:
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. CoRR abs/1907.10994 (2019) - [i3]Gabriel Kalweit, Maria Hügle, Joschka Boedecker:
Off-policy Multi-step Q-learning. CoRR abs/1909.13518 (2019) - [i2]Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. CoRR abs/1909.13582 (2019) - [i1]Oier Mees, Markus Merklinger, Gabriel Kalweit, Wolfram Burgard:
Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. CoRR abs/1910.09430 (2019) - 2017
- [c1]Gabriel Kalweit, Joschka Boedecker:
Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning. CoRL 2017: 195-206
Coauthor Index
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