Philip Becker-Ehmck

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Patrick van der SmagtVolkswagen AG; ELTE UniversityVerified email at tum.de
Maximilian KarlResearch Scientist, Machine Learning Research Lab, Volkswagen GroupVerified email at in.tum.de
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
Justin BayerVolkswagen AGVerified email at volkswagen.de
Maximilian SoelchMachine Learning Research Lab, Volkswagen AGVerified email at argmax.ai
Djalel BenbouzidMachine Learnig Research Lab, Volkswagen GroupVerified email at argmax.ai
Neha DasDoctoral Candidate, Technical University of MunichVerified email at tum.de
Xingyuan Zhang (张兴远)Machine Learning Research Lab, Volkswagen AG; Technical University of MunichVerified email at tum.de

Philip Becker-Ehmck

Volkswagen Group

Verified email at volkswagen.de


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Switching Linear Dynamics for Variational Bayes Filtering P Becker-Ehmck, J Peters, P van der Smagt 36th International Conference on Machine Learning (ICML), 2018	60	2018
Unsupervised real-time control through variational empowerment M Karl, P Becker-Ehmck, M Soelch, D Benbouzid, P van der Smagt, ... The International Symposium of Robotics Research, 158-173, 2019	59	2019
Learning to Fly via Deep Model-Based Reinforcement Learning P Becker-Ehmck, M Karl, J Peters, P van der Smagt arXiv preprint arXiv:2003.08876, 2020	44	2020
Exploration via Empowerment Gain: Combining Novelty, Surprise and Learning Progress P Becker-Ehmck, M Karl, J Peters, P van der Smagt ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021	6	2021
Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations N Das, M Karl, P Becker-Ehmck, P van der Smagt arXiv preprint arXiv:1911.00756, 2019	5	2019
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models X Zhang, P Becker-Ehmck, P van der Smagt, M Karl Thirty-Seventh Conference on Advances in Neural Information Processing Systems, 2023	1	2023
Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models X Zhang, P Becker-Ehmck, P van der Smagt, M Karl arXiv preprint arXiv:2404.18896, 2024		2024
Latent State-Space Models for Control P Becker-Ehmck Technische Universität Darmstadt, 2022		2022

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