First steps towards the development of the sense of object permanence in robots. - Sarah Bechtle; Guido Schillaci; Verena V. Hafner (ICDL-EPIROB, 2015)

On the sense of agency and of object permanence in robots. - Sarah Bechtle; Guido Schillaci; Verena V. Hafner (ICDL-EPIROB, 2016)

Towards a humanoid-oriented movement writing. - Adrian Stoica; Hyung Ju Terry Suh; Steven M. Hewitt; Sarah Bechtle; Anna Gruebler; Yumi Iwashita (SMC, 2017)

Curious iLQR: Resolving Uncertainty in Model-based RL. - Sarah Bechtle; Yixin Lin; Akshara Rai; Ludovic Righetti; Franziska Meier (CoRL, 2019)

Meta-Learning via Learned Loss. - Yevgen Chebotar; Artem Molchanov; Sarah Bechtle; Ludovic Righetti; Franziska Meier; Gaurav S. Sukhatme (CoRR, 2019)

Model-Based Inverse Reinforcement Learning from Visual Demonstrations. - Neha Das; Sarah Bechtle; Todor Davchev; Dinesh Jayaraman; Akshara Rai; Franziska Meier (CoRL, 2020)

Meta Learning via Learned Loss. - Sarah Bechtle; Artem Molchanov; Yevgen Chebotar; Edward Grefenstette; Ludovic Righetti; Gaurav S. Sukhatme; Franziska Meier (ICPR, 2020)

Learning Extended Body Schemas from Visual Keypoints for Object Manipulation. - Sarah Bechtle; Neha Das; Franziska Meier (CoRR, 2020)

Leveraging Forward Model Prediction Error for Learning Control. - Sarah Bechtle; Bilal Hammoud; Akshara Rai; Franziska Meier; Ludovic Righetti (ICRA, 2021)

Learning Time-Invariant Reward Functions through Model-Based Inverse Reinforcement Learning. - Todor Davchev; Sarah Bechtle; Subramanian Ramamoorthy; Franziska Meier (CoRR, 2021)

Model Based Meta Learning of Critics for Policy Gradients. - Sarah Bechtle; Ludovic Righetti; Franziska Meier (CoRR, 2022)

A Generalist Dynamics Model for Control. - Ingmar Schubert; Jingwei Zhang 001; Jake Bruce; Sarah Bechtle; Emilio Parisotto; Martin A. Riedmiller; Jost Tobias Springenberg; Arunkumar Byravan; Leonard Hasenclever; Nicolas Heess (CoRR, 2023)

Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning. - Cristina Pinneri; Sarah Bechtle; Markus Wulfmeier; Arunkumar Byravan; Jingwei Zhang 001; William F. Whitney; Martin A. Riedmiller (CoRR, 2023)

Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities. - Markus Wulfmeier; Arunkumar Byravan; Sarah Bechtle; Karol Hausman; Nicolas Heess (CoRR, 2023)

Multimodal Learning of Keypoint Predictive Models for Visual Object Manipulation. - Sarah Bechtle; Neha Das; Franziska Meier (IEEE Trans. Robotics, 2023)

Genie: Generative Interactive Environments. - Jake Bruce; Michael D. Dennis; Ashley Edwards; Jack Parker-Holder; Yuge Shi; Edward Hughes 001; Matthew Lai; Aditi Mavalankar; Richie Steigerwald; Chris Apps; Yusuf Aytar; Sarah Bechtle; et al. (ICML, 2024)

Offline Actor-Critic Reinforcement Learning Scales to Large Models. - Jost Tobias Springenberg; Abbas Abdolmaleki; Jingwei Zhang 001; Oliver Groth; Michael Bloesch; Thomas Lampe; Philemon Brakel; Sarah Bechtle; Steven Kapturowski; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (ICML, 2024)

Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. - Thomas Lampe; Abbas Abdolmaleki; Sarah Bechtle; Sandy H. Huang; Jost Tobias Springenberg; Michael Bloesch; Oliver Groth; Roland Hafner; Tim Hertweck; Michael Neunert; Markus Wulfmeier; Jingwei Zhang 001; et al. (ICRA, 2024)

Imitating Language via Scalable Inverse Reinforcement Learning. - Markus Wulfmeier; Michael Bloesch; Nino Vieillard; Arun Ahuja; Jörg Bornschein; Sandy H. Huang; Artem Sokolov; Matt Barnes 001; Guillaume Desjardins; Alex Bewley; Sarah Bechtle; Jost Tobias Springenberg; et al. (NeurIPS, 2024)