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L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization., , , , , , and . CoRR, (2023)Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning., , , and . CoRR, (2023)Deep Surrogate Q-Learning for Autonomous Driving., , , and . ICRA, page 1578-1584. IEEE, (2022)Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection., , , , , , , and . EMBC, page 2268-2271. IEEE, (2018)Acting thoughts: Towards a mobile robotic service assistant for users with limited communication skills., , , , , , , , , and 1 other author(s). ECMR, page 1-6. IEEE, (2017)Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression., , , , and . Robotics: Science and Systems, (2012)Latent Linear Quadratic Regulator for Robotic Control Tasks., , , , and . CoRR, (2024)Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving., , , and . CoRR, (2020)Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving., , , and . CoRR, (2023)Robot motion description and real-time management with the Harmonic Motion Description Protocol., , and . Robotics Auton. Syst., 57 (8): 870-876 (2009)