Learning predictive models of a depth camera & manipulator from raw execution traces. - Byron Boots; Arunkumar Byravan; Dieter Fox (ICRA, 2014)

Space-time functional gradient optimization for motion planning. - Arunkumar Byravan; Byron Boots; Siddhartha S. Srinivasa; Dieter Fox (ICRA, 2014)

Graph-Based Inverse Optimal Control for Robot Manipulation. - Arunkumar Byravan; Mathew Monfort; Brian D. Ziebart; Byron Boots; Dieter Fox (IJCAI, 2015)

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. - Zita Marinho; Byron Boots; Anca D. Dragan; Arunkumar Byravan; Geoffrey J. Gordon; Siddhartha S. Srinivasa (Robotics: Science and Systems, 2016)

SE3-nets: Learning rigid body motion using deep neural networks. - Arunkumar Byravan; Dieter Fox (ICRA, 2017)

SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control. - Arunkumar Byravan; Felix Leeb; Franziska Meier; Dieter Fox (CoRR, 2017)

SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Control. - Arunkumar Byravan; Felix Leeb; Franziska Meier; Dieter Fox (ICRA, 2018)

Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. - Arunkumar Byravan; Jost Tobias Springenberg; Abbas Abdolmaleki; Roland Hafner; Michael Neunert; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRL, 2019)

Prospection: Interpretable plans from language by predicting the future. - Chris Paxton 001; Yonatan Bisk; Jesse Thomason; Arunkumar Byravan; Dieter Fox (ICRA, 2019)

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. - Arunkumar Byravan; Jost Tobias Springenberg; Abbas Abdolmaleki; Roland Hafner; Michael Neunert; Thomas Lampe; Noah Y. Siegel; Nicolas Heess; Martin A. Riedmiller (CoRR, 2019)

Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB. - Felix Leeb; Arunkumar Byravan; Dieter Fox (CoRR, 2019)

Structured Deep Visual Dynamics Models for Robot Manipulation. - Arunkumar Byravan (2019)

Local Search for Policy Iteration in Continuous Control. - Jost Tobias Springenberg; Nicolas Heess; Daniel J. Mankowitz; Josh Merel; Arunkumar Byravan; Abbas Abdolmaleki; Jackie Kay; Jonas Degrave; Julian Schrittwieser; Yuval Tassa; Jonas Buchli; Dan Belov; et al. (CoRR, 2020)

Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. - Michael Bloesch; Jan Humplik; Viorica Patraucean; Roland Hafner; Tuomas Haarnoja; Arunkumar Byravan; Noah Yamamoto Siegel; Saran Tunyasuvunakool; Federico Casarini; Nathan Batchelor; Francesco Romano; Stefano Saliceti; et al. (CoRL, 2021)

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. - Alex X. Lee; Coline Manon Devin; Yuxiang Zhou; Thomas Lampe; Konstantinos Bousmalis; Jost Tobias Springenberg; Arunkumar Byravan; Abbas Abdolmaleki; Nimrod Gileadi; David Khosid; Claudio Fantacci; José Enrique Chen; et al. (CoRL, 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)

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. - Abbas Abdolmaleki; Sandy H. Huang; Giulia Vezzani; Bobak Shahriari; Jost Tobias Springenberg; Shruti Mishra; Dhruva TB; Arunkumar Byravan; Konstantinos Bousmalis; András György 001; Csaba Szepesvári; Raia Hadsell; et al. (CoRR, 2021)

Learning Dynamics Models for Model Predictive Agents. - Michael Lutter; Leonard Hasenclever; Arunkumar Byravan; Gabriel Dulac-Arnold; Piotr Trochim; Nicolas Heess; Josh Merel; Yuval Tassa (CoRR, 2021)

Evaluating Model-Based Planning and Planner Amortization for Continuous Control. - Arunkumar Byravan; Leonard Hasenclever; Piotr Trochim; Mehdi Mirza; Alessandro Davide Ialongo; Yuval Tassa; Jost Tobias Springenberg; Abbas Abdolmaleki; Nicolas Heess; Josh Merel; Martin A. Riedmiller (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)

Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. - Bobak Shahriari; Abbas Abdolmaleki; Arunkumar Byravan; Abe Friesen; Siqi Liu 002; Jost Tobias Springenberg; Nicolas Heess; Matt Hoffman 001; Martin A. Riedmiller (CoRR, 2022)

NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. - Arunkumar Byravan; Jan Humplik; Leonard Hasenclever; Arthur Brussee; Francesco Nori; Tuomas Haarnoja; Ben Moran; Steven Bohez; Fereshteh Sadeghi; Bojan Vujatovic; Nicolas Heess (ICRA, 2023)

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)

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)

Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning. - Norman Di Palo; Leonard Hasenclever; Jan Humplik; Arunkumar Byravan (CoLLAs, 2024)

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)

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)

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)

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. - Connor Schenck; Isaac Reid; Mithun George Jacob; Alex Bewley; Joshua Ainslie; David Rendleman; Deepali Jain; Mohit Sharma 001; Avinava Dubey; Ayzaan Wahid; Sumeet Singh; René Wagner; et al. (CoRR, 2025)

Proc4Gem: Foundation models for physical agency through procedural generation. - Yixin Lin; Jan Humplik; Sandy H. Huang; Leonard Hasenclever; Francesco Romano; Stefano Saliceti; Daniel Zheng; José Enrique Chen; Catarina Barros; Adrian Collister; Matt Young; Adil Dostmohamed; et al. (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)

Splatting Physical Scenes: End-to-End Real-to-Sim from Imperfect Robot Data. - Ben Moran; Mauro Comi; Arunkumar Byravan; Steven Bohez; Tom Erez; Zhibin Li; Leonard Hasenclever (CoRR, 2025)