Tim Seyde

Orcid: 0000-0001-9592-4465

According to our database1, Tim Seyde authored at least 17 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Cooperative Flight Control Using Visual-Attention.
IROS, 2023

Solving Continuous Control via Q-learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation.
Proceedings of the Conference on Robot Learning, 2023

Measuring Interpretability of Neural Policies of Robots with Disentangled Representation.
Proceedings of the Conference on Robot Learning, 2023

2022
Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies.
IEEE Robotics Autom. Lett., 2022

Cooperative Flight Control Using Visual-Attention - Air-Guardian.
CoRR, 2022

Interpreting Neural Policies with Disentangled Tree Representations.
CoRR, 2022

Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Autonomous Flight Arcade Challenge: Single- and Multi-Agent Learning Environments for Aerial Vehicles.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Strength Through Diversity: Robust Behavior Learning via Mixture Policies.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Learning to Plan via Deep Optimistic Value Exploration.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Locomotion Planning through a Hybrid Bayesian Trajectory Optimization.
Proceedings of the International Conference on Robotics and Automation, 2019

2018
Inclusion of Angular Momentum During Planning for Capture Point Based Walking.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018


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