Karl, Maximilian

8 publications

TMLR 2025 Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

NeurIPS 2024 Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning Marvin Alles, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

ICMLW 2024 Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

NeurIPS 2023 Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

ICLRW 2023 Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

L4DC 2023 CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces Elie Aljalbout, Maximilian Karl, Patrick van der Smagt

ICMLW 2021 Exploration via Empowerment Gain: Combining Novelty, Surprise and Learning Progress Philip Becker-Ehmck, Maximilian Karl, Jan Peters, Patrick van der Smagt

ICLR 2017 Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt