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Tim Seyde
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2020 – today
- 2024
- [c15]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 - [i9]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
- [c14]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 - [c13]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 - [c12]Tim Seyde, Peter Werner, Wilko Schwarting, Igor Gilitschenski, Martin A. Riedmiller, Daniela Rus, Markus Wulfmeier:
Solving Continuous Control via Q-learning. ICLR 2023 - [c11]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 - [c10]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
- [j1]Paul Tylkin
, Tsun-Hsuan Wang
Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies. IEEE Robotics Autom. Lett. 7(2): 3265-3272 (2022) - [c9]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 - [c8]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 - [i8]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) - [i7]Tsun-Hsuan Wang, Wei Xiao, Tim Seyde, Ramin M. Hasani, Daniela Rus:
Interpreting Neural Policies with Disentangled Tree Representations. CoRR abs/2210.06650 (2022) - [i6]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) - [i5]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
- [c7]Tim Seyde, Wilko Schwarting, Igor Gilitschenski, Markus Wulfmeier, Daniela Rus:
Strength Through Diversity: Robust Behavior Learning via Mixture Policies. CoRL 2021: 1144-1155 - [c6]Tim Seyde, Wilko Schwarting, Sertac Karaman, Daniela Rus:
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles. CoRL 2021: 1156-1167 - [c5]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 - [i4]Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. CoRR abs/2102.09812 (2021) - [i3]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
- [c4]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 - [c3]Tim Seyde, Wilko Schwarting, Sertac Karaman, Daniela Rus:
Learning to Plan via Deep Optimistic Value Exploration. L4DC 2020: 815-825 - [i2]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)
2010 – 2019
- 2019
- [c2]Tim Seyde, Jan Carius, Ruben Grandia, Farbod Farshidian, Marco Hutter:
Locomotion Planning through a Hybrid Bayesian Trajectory Optimization. ICRA 2019: 5544-5550 - [i1]Tim Seyde, Jan Carius, Ruben Grandia, Farbod Farshidian, Marco Hutter:
Locomotion Planning through a Hybrid Bayesian Trajectory Optimization. CoRR abs/1903.03823 (2019) - 2018
- [c1]Tim Seyde, Apoorv Shrivastava, Johannes Englsberger
Inclusion of Angular Momentum During Planning for Capture Point Based Walking. ICRA 2018: 1791-1798
Coauthor Index
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