Inclusion of Angular Momentum During Planning for Capture Point Based Walking. - Tim Seyde; Apoorv Shrivastava; Johannes Englsberger; Sylvain Bertrand; Jerry E. Pratt; Robert J. Griffin (ICRA, 2018)

Locomotion Planning through a Hybrid Bayesian Trajectory Optimization. - Tim Seyde; Jan Carius; Ruben Grandia; Farbod Farshidian; Marco Hutter 001 (ICRA, 2019)

Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. - Wilko Schwarting; Tim Seyde; Igor Gilitschenski; Lucas Liebenwein; Ryan Sander; Sertac Karaman; Daniela Rus (CoRL, 2020)

Learning to Plan via Deep Optimistic Value Exploration. - Tim Seyde; Wilko Schwarting; Sertac Karaman; Daniela Rus (L4DC, 2020)

Strength Through Diversity: Robust Behavior Learning via Mixture Policies. - Tim Seyde; Wilko Schwarting; Igor Gilitschenski; Markus Wulfmeier; Daniela Rus (CoRL, 2021)

Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles. - Tim Seyde; Wilko Schwarting; Sertac Karaman; Daniela Rus (CoRL, 2021)

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. - Tim Seyde; Igor Gilitschenski; Wilko Schwarting; Bartolomeo Stellato; Martin A. Riedmiller; Markus Wulfmeier; Daniela Rus (NeurIPS, 2021)

Autonomous Flight Arcade Challenge: Single- and Multi-Agent Learning Environments for Aerial Vehicles. - Paul Tylkin; Tsun-Hsuan Wang; Tim Seyde; Kyle Palko; Ross E. Allen; Alexander Amini; Daniela Rus (AAMAS, 2022)

Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks. - Ryan Sander; Wilko Schwarting; Tim Seyde; Igor Gilitschenski; Sertac Karaman; Daniela Rus (L4DC, 2022)

Interpreting Neural Policies with Disentangled Tree Representations. - Tsun-Hsuan Wang; Wei Xiao 003; Tim Seyde; Ramin M. Hasani; Daniela Rus (CoRR, 2022)

Cooperative Flight Control Using Visual-Attention - Air-Guardian. - Lianhao Yin; Tsun-Hsuan Wang; Makram Chahine; Tim Seyde; Mathias Lechner; Ramin M. Hasani; Daniela Rus (CoRR, 2022)

Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies. - Paul Tylkin; Tsun-Hsuan Wang; Kyle Palko; Ross E. Allen; Ho Chit Siu; Daniel Wrafter; Tim Seyde; Alexander Amini; Daniela Rus (IEEE Robotics Autom. Lett., 2022)

Measuring Interpretability of Neural Policies of Robots with Disentangled Representation. - Tsun-Hsuan Wang; Wei Xiao 003; Tim Seyde; Ramin M. Hasani; Daniela Rus (CoRL, 2023)

Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation. - Peter Werner; Tim Seyde; Paul Drews; Thomas Matrai Balch; Igor Gilitschenski; Wilko Schwarting; Guy Rosman; Sertac Karaman; Daniela Rus (CoRL, 2023)

Solving Continuous Control via Q-learning. - Tim Seyde; Peter Werner; Wilko Schwarting; Igor Gilitschenski; Martin A. Riedmiller; Daniela Rus; Markus Wulfmeier (ICLR, 2023)

Towards Cooperative Flight Control Using Visual-Attention. - Lianhao Yin; Makram Chahine; Tsun-Hsuan Wang; Tim Seyde; Chao Liu 021; Mathias Lechner; Ramin M. Hasani; Daniela Rus (IROS, 2023)

Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning. - Mathias Lechner; Lianhao Yin; Tim Seyde; Tsun-Hsuan Johnson Wang; Wei Xiao 003; Ramin M. Hasani; Joshua Rountree; Daniela Rus (NeurIPS, 2023)

Competitive Multi-Team Behavior in Dynamic Flight Scenarios. - Tim Seyde; Mathias Lechner; Joshua Rountree; Daniela Rus (IROS, 2024)

Growing Q-networks: Solving continuous control tasks with adaptive control resolution. - Tim Seyde; Peter Werner; Wilko Schwarting; Markus Wulfmeier; Daniela Rus (L4DC, 2024)

Faster Algorithms for Growing Collision-Free Convex Polytopes in Robot Configuration Space. - Peter Werner; Thomas Cohn; Rebecca H. Jiang; Tim Seyde; Max Simchowitz; Russ Tedrake; Daniela Rus (CoRR, 2024)