Voronoi-Based Heuristic for Nonholonomic Search-Based Path Planning. - Qi Wang 081; Markus Wulfmeier; Bernardo Wagner (IAS, 2014)

Deep Inverse Reinforcement Learning. - Markus Wulfmeier; Peter Ondruska; Ingmar Posner (CoRR, 2015)

Watch this: Scalable cost-function learning for path planning in urban environments. - Markus Wulfmeier; Dominic Zeng Wang; Ingmar Posner (IROS, 2016)

Incorporating Human Domain Knowledge into Large Scale Cost Function Learning. - Markus Wulfmeier; Dushyant Rao; Ingmar Posner (CoRR, 2016)

Reverse Curriculum Generation for Reinforcement Learning. - Carlos Florensa; David Held; Markus Wulfmeier; Michael Zhang; Pieter Abbeel (CoRL, 2017)

Mutual Alignment Transfer Learning. - Markus Wulfmeier; Ingmar Posner; Pieter Abbeel (CoRL, 2017)

Addressing appearance change in outdoor robotics with adversarial domain adaptation. - Markus Wulfmeier; Alex Bewley; Ingmar Posner (IROS, 2017)

Reverse Curriculum Generation for Reinforcement Learning. - Carlos Florensa; David Held; Markus Wulfmeier; Pieter Abbeel (CoRR, 2017)

Incremental Adversarial Domain Adaptation. - Markus Wulfmeier; Alex Bewley; Ingmar Posner (CoRR, 2017)

Large-scale cost function learning for path planning using deep inverse reinforcement learning. - Markus Wulfmeier; Dushyant Rao; Dominic Zeng Wang; Peter Ondruska; Ingmar Posner (Int. J. Robotics Res., 2017)

TACO: Learning Task Decomposition via Temporal Alignment for Control. - Kyriacos Shiarlis; Markus Wulfmeier; Sasha Salter; Shimon Whiteson; Ingmar Posner (ICML, 2018)

Incremental Adversarial Domain Adaptation for Continually Changing Environments. - Markus Wulfmeier; Alex Bewley; Ingmar Posner (ICRA, 2018)

Neural Stethoscopes: Unifying Analytic, Auxiliary and Adversarial Network Probing. - Fabian B. Fuchs; Oliver Groth; Adam R. Kosiorek; Alex Bewley; Markus Wulfmeier; Andrea Vedaldi; Ingmar Posner (CoRR, 2018)

On Machine Learning and Structure for Mobile Robots. - Markus Wulfmeier (CoRR, 2018)

Efficient supervision for robot learning via imitation, simulation, and adaptation. - Markus Wulfmeier (2018)

Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes. - Fabian B. Fuchs; Oliver Groth; Adam R. Kosiorek; Alex Bewley; Markus Wulfmeier; Andrea Vedaldi; Ingmar Posner (BMVC, 2019)

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. - Michael Neunert; Abbas Abdolmaleki; Markus Wulfmeier; Thomas Lampe; Jost Tobias Springenberg; Roland Hafner; Francesco Romano; Jonas Buchli; Nicolas Heess; Martin A. Riedmiller (CoRL, 2019)

Regularized Hierarchical Policies for Compositional Transfer in Robotics. - Markus Wulfmeier; Abbas Abdolmaleki; Roland Hafner; Jost Tobias Springenberg; Michael Neunert; Tim Hertweck; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRR, 2019)

Attention Privileged Reinforcement Learning For Domain Transfer. - Sasha Salter; Dushyant Rao; Markus Wulfmeier; Raia Hadsell; Ingmar Posner (CoRR, 2019)

Disentangled Cumulants Help Successor Representations Transfer to New Tasks. - Christopher Grimm; Irina Higgins; André Barreto 001; Denis Teplyashin; Markus Wulfmeier; Tim Hertweck; Raia Hadsell; Satinder Singh 001 (CoRR, 2019)

Efficient Supervision for Robot Learning Via Imitation, Simulation, and Adaptation. - Markus Wulfmeier (Künstliche Intell., 2019)

Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. - Roland Hafner; Tim Hertweck; Philipp Klöppner; Michael Bloesch; Michael Neunert; Markus Wulfmeier; Saran Tunyasuvunakool; Nicolas Heess; Martin A. Riedmiller (CoRL, 2020)

Attention-Privileged Reinforcement Learning. - Sasha Salter; Dushyant Rao; Markus Wulfmeier; Raia Hadsell; Ingmar Posner (CoRL, 2020)

Compositional Transfer in Hierarchical Reinforcement Learning. - Markus Wulfmeier; Abbas Abdolmaleki; Roland Hafner; Jost Tobias Springenberg; Michael Neunert; Noah Y. Siegel; Tim Hertweck; Thomas Lampe; Nicolas Heess; Martin A. Riedmiller (Robotics: Science and Systems, 2020)

Simple Sensor Intentions for Exploration. - Tim Hertweck; Martin A. Riedmiller; Michael Bloesch; Jost Tobias Springenberg; Noah Y. Siegel; Markus Wulfmeier; Roland Hafner; Nicolas Heess (CoRR, 2020)

"What, not how": Solving an under-actuated insertion task from scratch. - Giulia Vezzani; Michael Neunert; Markus Wulfmeier; Rae Jeong; Thomas Lampe; Noah Y. Siegel; Roland Hafner; Abbas Abdolmaleki; Martin A. Riedmiller; Francesco Nori (CoRR, 2020)

Strength Through Diversity: Robust Behavior Learning via Mixture Policies. - Tim Seyde; Wilko Schwarting; Igor Gilitschenski; Markus Wulfmeier; Daniela Rus (CoRL, 2021)

Data-efficient Hindsight Off-policy Option Learning. - Markus Wulfmeier; Dushyant Rao; Roland Hafner; Thomas Lampe; Abbas Abdolmaleki; Tim Hertweck; Michael Neunert; Dhruva Tirumala; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (ICML, 2021)

Representation Matters: Improving Perception and Exploration for Robotics. - Markus Wulfmeier; Arunkumar Byravan; Tim Hertweck; Irina Higgins; Ankush Gupta; Tejas Kulkarni; Malcolm Reynolds; Denis Teplyashin; Roland Hafner; Thomas Lampe; Martin A. Riedmiller (ICRA, 2021)

Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. - Nico Gürtler; Felix Widmaier; Cansu Sancaktar; Sebastian Blaes; Pavel Kolev; Stefan Bauer; Manuel Wüthrich; Markus Wulfmeier; Martin A. Riedmiller; Arthur Allshire; Qiang Wang; Robert McCarthy; et al. (NeurIPS (Competition and Demos), 2021)

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. - Tim Seyde; Igor Gilitschenski; Wilko Schwarting; Bartolomeo Stellato; Martin A. Riedmiller; Markus Wulfmeier; Daniela Rus (NeurIPS, 2021)

Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration. - Oliver Groth; Markus Wulfmeier; Giulia Vezzani; Vibhavari Dasagi; Tim Hertweck; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (CoRR, 2021)

MO2: Model-Based Offline Options. - Sasha Salter; Markus Wulfmeier; Dhruva Tirumala; Nicolas Heess; Martin A. Riedmiller; Raia Hadsell; Dushyant Rao (CoLLAs, 2022)

Forgetting and Imbalance in Robot Lifelong Learning with Off-policy Data. - Wenxuan Zhou; Steven Bohez; Jan Humplik; Nicolas Heess; Abbas Abdolmaleki; Dushyant Rao; Markus Wulfmeier; Tuomas Haarnoja (CoLLAs, 2022)

Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation. - Todor Davchev; Oleg Olegovich Sushkov; Jean-Baptiste Regli; Stefan Schaal; Yusuf Aytar; Markus Wulfmeier; Jon Scholz (ICLR, 2022)

Learning transferable motor skills with hierarchical latent mixture policies. - Dushyant Rao; Fereshteh Sadeghi; Leonard Hasenclever; Markus Wulfmeier; Martina Zambelli; Giulia Vezzani; Dhruva Tirumala; Yusuf Aytar; Josh Merel; Nicolas Heess; Raia Hadsell (ICLR, 2022)

The Challenges of Exploration for Offline Reinforcement Learning. - Nathan Lambert 001; Markus Wulfmeier; William F. Whitney; Arunkumar Byravan; Michael Bloesch; Vibhavari Dasagi; Tim Hertweck; Martin A. Riedmiller (CoRR, 2022)

Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors. - Steven Bohez; Saran Tunyasuvunakool; Philemon Brakel; Fereshteh Sadeghi; Leonard Hasenclever; Yuval Tassa; Emilio Parisotto; Jan Humplik; Tuomas Haarnoja; Roland Hafner; Markus Wulfmeier; Michael Neunert; et al. (CoRR, 2022)

Offline Distillation for Robot Lifelong Learning with Imbalanced Experience. - Wenxuan Zhou; Steven Bohez; Jan Humplik; Abbas Abdolmaleki; Dushyant Rao; Markus Wulfmeier; Tuomas Haarnoja; Nicolas Heess (CoRR, 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 2022)

Solving Continuous Control via Q-learning. - Tim Seyde; Peter Werner; Wilko Schwarting; Igor Gilitschenski; Martin A. Riedmiller; Daniela Rus; Markus Wulfmeier (ICLR, 2023)

Towards A Unified Agent with Foundation Models. - Norman Di Palo; Arunkumar Byravan; Leonard Hasenclever; Markus Wulfmeier; Nicolas Heess; Martin A. Riedmiller (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)

SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration. - Giulia Vezzani; Dhruva Tirumala; Markus Wulfmeier; Dushyant Rao; Abbas Abdolmaleki; Ben Moran; Tuomas Haarnoja; Jan Humplik; Roland Hafner; Michael Neunert; Claudio Fantacci; Tim Hertweck; et al. (Trans. Mach. Learn. Res., 2023)

Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. - Dhruva Tirumala; Markus Wulfmeier; Ben Moran; Sandy H. Huang; Jan Humplik; Guy Lever; Tuomas Haarnoja; Leonard Hasenclever; Arunkumar Byravan; Nathan Batchelor; Neil Sreendra; Kushal Patel; et al. (CoRL, 2024)

Massively Scalable Inverse Reinforcement Learning in Google Maps. - Matt Barnes 001; Matthew Abueg; Oliver F. Lange; Matt Deeds; Jason Trader; Denali Molitor; Markus Wulfmeier; Shawn O'Banion (ICLR, 2024)

Replay across Experiments: A Natural Extension of Off-Policy RL. - Dhruva Tirumala; Thomas Lampe; José Enrique Chen; Tuomas Haarnoja; Sandy H. Huang; Guy Lever; Ben Moran; Tim Hertweck; Leonard Hasenclever; Martin A. Riedmiller; Nicolas Heess; Markus Wulfmeier (ICLR, 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)

Real-world fluid directed rigid body control via deep reinforcement learning. - Mohak Bhardwaj; Thomas Lampe; Michael Neunert; Francesco Romano; Abbas Abdolmaleki; Arunkumar Byravan; Markus Wulfmeier; Martin A. Riedmiller; Jonas Buchli (L4DC, 2024)

Growing Q-networks: Solving continuous control tasks with adaptive control resolution. - Tim Seyde; Peter Werner; Wilko Schwarting; Markus Wulfmeier; Daniela Rus (L4DC, 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)

Learning agile soccer skills for a bipedal robot with deep reinforcement learning. - Tuomas Haarnoja; Ben Moran; Guy Lever; Sandy H. Huang; Dhruva Tirumala; Jan Humplik; Markus Wulfmeier; Saran Tunyasuvunakool; Noah Y. Siegel; Roland Hafner; Michael Bloesch; Kristian Hartikainen; et al. (Sci. Robotics, 2024)

Data Release for: Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. - Tuomas Haarnoja; Ben Moran; Guy Lever; Sandy H. Huang; Dhruva Tirumala; Jan Humplik; Markus Wulfmeier; Saran Tunyasuvunakool; Noah Y. Siegel; Roland Hafner; Michael Bloesch; Kristian Hartikainen; et al. (Zenodo, 2024)

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities. - Thomas Schmied; Jörg Bornschein; Jordi Grau-Moya; Markus Wulfmeier; Razvan Pascanu (CoRR, 2025)

The AI Imperative: Scaling High-Quality Peer Review in Machine Learning. - Qiyao Wei; Samuel Holt; Jing Yang; Markus Wulfmeier; Mihaela van der Schaar (CoRR, 2025)

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs. - Sonia K. Murthy; Rosie Zhao; Jennifer Hu 001; Sham M. Kakade; Markus Wulfmeier; Peng Qian; Tomer D. Ullman (CoRR, 2025)

Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement. - Michael Bloesch; Markus Wulfmeier; Philemon Brakel; Todor Davchev; Martina Zambelli; Jost Tobias Springenberg; Abbas Abdolmaleki; William F. Whitney; Nicolas Heess; Roland Hafner; Martin A. Riedmiller (CoRR, 2025)

Exploiting Policy Idling for Dexterous Manipulation. - Annie S. Chen; Philemon Brakel; Antonia Bronars; Annie Xie; Sandy H. Huang; Oliver Groth; Maria Bauzá 001; Markus Wulfmeier; Nicolas Heess; Dushyant Rao (CoRR, 2025)