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Publication search results
found 27 matches
- 2024
- Tim Seyde, Peter Werner, Wilko Schwarting, Markus Wulfmeier, Daniela Rus:
Growing Q-networks: Solving continuous control tasks with adaptive control resolution. L4DC 2024: 1646-1661 - Tim Seyde, Peter Werner, Wilko Schwarting, Markus Wulfmeier, Daniela Rus:
Growing Q-Networks: Solving Continuous Control Tasks with Adaptive Control Resolution. CoRR abs/2404.04253 (2024) - 2023
- Tsun-Hsuan Wang, Wei Xiao, Tim Seyde, Ramin M. Hasani, Daniela Rus:
Measuring Interpretability of Neural Policies of Robots with Disentangled Representation. CoRL 2023: 602-641 - Peter Werner, Tim Seyde, Paul Drews, Thomas Matrai Balch, Igor Gilitschenski, Wilko Schwarting, Guy Rosman, Sertac Karaman, Daniela Rus:
Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation. CoRL 2023: 1667-1685 - Tim Seyde, Peter Werner, Wilko Schwarting, Igor Gilitschenski, Martin A. Riedmiller, Daniela Rus, Markus Wulfmeier:
Solving Continuous Control via Q-learning. ICLR 2023 - Lianhao Yin, Makram Chahine, Tsun-Hsuan Wang, Tim Seyde, Chao Liu, Mathias Lechner, Ramin M. Hasani, Daniela Rus:
Towards Cooperative Flight Control Using Visual-Attention. IROS 2023: 6334-6341 - Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Johnson Wang, Wei Xiao, Ramin M. Hasani, Joshua Rountree, Daniela Rus:
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning. NeurIPS 2023 - 2022
- Paul Tylkin
, Tsun-Hsuan Wang
, Kyle Palko
, Ross E. Allen
, Ho Chit Siu, Daniel Wrafter, Tim Seyde
, Alexander Amini
, Daniela Rus
:
Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies. IEEE Robotics Autom. Lett. 7(2): 3265-3272 (2022) - Paul Tylkin, Tsun-Hsuan Wang, Tim Seyde, Kyle Palko, Ross E. Allen, Alexander Amini, Daniela Rus:
Autonomous Flight Arcade Challenge: Single- and Multi-Agent Learning Environments for Aerial Vehicles. AAMAS 2022: 1744-1746 - Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman, Daniela Rus:
Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks. L4DC 2022: 954-967 - Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman, Daniela Rus:
Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks. CoRR abs/2205.09117 (2022) - Tsun-Hsuan Wang, Wei Xiao, Tim Seyde, Ramin M. Hasani, Daniela Rus:
Interpreting Neural Policies with Disentangled Tree Representations. CoRR abs/2210.06650 (2022) - Tim Seyde, Peter Werner, Wilko Schwarting, Igor Gilitschenski, Martin A. Riedmiller, Daniela Rus, Markus Wulfmeier:
Solving Continuous Control via Q-learning. CoRR abs/2210.12566 (2022) - Lianhao Yin, Tsun-Hsuan Wang, Makram Chahine, Tim Seyde, Mathias Lechner, Ramin M. Hasani, Daniela Rus:
Cooperative Flight Control Using Visual-Attention - Air-Guardian. CoRR abs/2212.11084 (2022) - 2021
- Tim Seyde, Wilko Schwarting, Igor Gilitschenski, Markus Wulfmeier, Daniela Rus:
Strength Through Diversity: Robust Behavior Learning via Mixture Policies. CoRL 2021: 1144-1155 - Tim Seyde, Wilko Schwarting, Sertac Karaman, Daniela Rus:
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles. CoRL 2021: 1156-1167 - Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin A. Riedmiller, Markus Wulfmeier, Daniela Rus:
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. NeurIPS 2021: 27209-27221 - Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander
, Sertac Karaman, Daniela Rus:
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. CoRR abs/2102.09812 (2021) - Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin A. Riedmiller, Markus Wulfmeier, Daniela Rus:
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. CoRR abs/2111.02552 (2021) - 2020
- Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Daniela Rus:
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. CoRL 2020: 1855-1870 - Tim Seyde, Wilko Schwarting, Sertac Karaman, Daniela Rus:
Learning to Plan via Deep Optimistic Value Exploration. L4DC 2020: 815-825 - Tim Seyde, Wilko Schwarting, Sertac Karaman, Daniela Rus:
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles. CoRR abs/2010.14641 (2020) - 2019
- Tim Seyde, Jan Carius, Ruben Grandia, Farbod Farshidian, Marco Hutter:
Locomotion Planning through a Hybrid Bayesian Trajectory Optimization. ICRA 2019: 5544-5550 - Tim Seyde, Jan Carius, Ruben Grandia, Farbod Farshidian, Marco Hutter:
Locomotion Planning through a Hybrid Bayesian Trajectory Optimization. CoRR abs/1903.03823 (2019) - 2018
- Tim Seyde, Apoorv Shrivastava, Johannes Englsberger
, Sylvain Bertrand, Jerry E. Pratt, Robert J. Griffin
:
Inclusion of Angular Momentum During Planning for Capture Point Based Walking. ICRA 2018: 1791-1798 - 2017
- Anna Seydel, Kimberly Farrell, Ross Johnson, Timothy Marler, Salam Rahmatalla, Rajan Bhatt, Karim Abdel-Malek:
Improved Motion Capture Processing for High-Fidelity Human Models Using Optimization-Based Prediction of Posture and Anthropometry. AHFE (7) 2017: 549-561 - 2016
- Christian Ott
, Bernd Henze, Georg Hettich, Tim Niklas Seyde, Máximo A. Roa
, Vittorio Lippi
, Thomas Mergner:
Good Posture, Good Balance: Comparison of Bioinspired and Model-Based Approaches for Posture Control of Humanoid Robots. IEEE Robotics Autom. Mag. 23(1): 22-33 (2016)
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retrieved on 2024-07-15 13:59 CEST from data curated by the dblp team
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