Deep reinforcement learning with successor features for navigation across similar environments. - Jingwei Zhang 001; Jost Tobias Springenberg; Joschka Boedecker; Wolfram Burgard (IROS, 2017)

Perspectives on Deep Multimodel Robot Learning. - Wolfram Burgard; Abhinav Valada; Noha Radwan; Tayyab Naseer; Jingwei Zhang 001; Johan Vertens; Oier Mees; Andreas Eitel; Gabriel L. Oliveira (ISRR, 2017)

Neural SLAM. - Jingwei Zhang 001; Lei Tai; Joschka Boedecker; Wolfram Burgard; Ming Liu 001 (CoRR, 2017)

Socially Compliant Navigation Through Raw Depth Inputs with Generative Adversarial Imitation Learning. - Lei Tai; Jingwei Zhang 001; Ming Liu 001; Wolfram Burgard (ICRA, 2018)

VR Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control. - Jingwei Zhang 001; Lei Tai; Yufeng Xiong; Ming Liu 001; Joschka Boedecker; Wolfram Burgard (CoRR, 2018)

Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning. - Oleksii Zhelo; Jingwei Zhang 001; Lei Tai; Ming Liu 001; Wolfram Burgard (CoRR, 2018)

Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration. - Jingwei Zhang 001; Niklas Wetzel; Nicolai Dorka; Joschka Boedecker; Wolfram Burgard (CoRR, 2019)

VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control. - Jingwei Zhang 001; Lei Tai; Peng Yun; Yufeng Xiong; Ming Liu 001; Joschka Boedecker; Wolfram Burgard (IEEE Robotics Autom. Lett., 2019)

Efficiency and Equity are Both Essential: A Generalized Traffic Signal Controller with Deep Reinforcement Learning. - Shengchao Yan; Jingwei Zhang 001; Daniel Büscher; Wolfram Burgard (IROS, 2020)

Learning navigation policies with deep reinforcement learning. - Jingwei Zhang 001 (2021)

Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. - Jingwei Zhang 001; Jost Tobias Springenberg; Arunkumar Byravan; Leonard Hasenclever; Abbas Abdolmaleki; Dushyant Rao; Nicolas Heess; Martin A. Riedmiller (CoRR, 2023)

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)

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)

Game On: Towards Language Models as RL Experimenters. - Jingwei Zhang 001; Thomas Lampe; Abbas Abdolmaleki; Jost Tobias Springenberg; Martin A. Riedmiller (CoRR, 2024)