Arunkumar Byravan

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 36

Top Topics

Reproducing Kernel

Rigid Body Motion

Reinforcement Learning

Top Venues

Publications

Norman Di Palo, Leonard Hasenclever, Jan Humplik, Arunkumar Byravan
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning. CoRR (2024)
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, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRR (2024)
Mohak Bhardwaj, Thomas Lampe, Michael Neunert, Francesco Romano, Abbas Abdolmaleki, Arunkumar Byravan, Markus Wulfmeier, Martin A. Riedmiller, Jonas Buchli
Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning. CoRR (2024)
Mohak Bhardwaj, Thomas Lampe, Michael Neunert, Francesco Romano, Abbas Abdolmaleki, Arunkumar Byravan, Markus Wulfmeier, Martin A. Riedmiller, Jonas Buchli
Real-world fluid directed rigid body control via deep reinforcement learning. L4DC (2024)
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, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics 9 (89) (2024)
Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess
A Generalist Dynamics Model for Control. CoRR (2023)
Cristina Pinneri, Sarah Bechtle, Markus Wulfmeier, Arunkumar Byravan, Jingwei Zhang, William F. Whitney, Martin A. Riedmiller
Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning. CoRR (2023)
Markus Wulfmeier, Arunkumar Byravan, Sarah Bechtle, Karol Hausman, Nicolas Heess
Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities. CoRR (2023)
Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. ICRA (2023)
Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin A. Riedmiller
Towards A Unified Agent with Foundation Models. CoRR (2023)
Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR (2023)
Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR (2023)
Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. CoRR (2022)
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
Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR (2022)
Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. CoRR (2022)
Nathan Lambert, Markus Wulfmeier, William F. Whitney, Arunkumar Byravan, Michael Bloesch, Vibhavari Dasagi, Tim Hertweck, Martin A. Riedmiller
The Challenges of Exploration for Offline Reinforcement Learning. CoRR (2022)
Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa
Learning Dynamics Models for Model Predictive Agents. CoRR (2021)
Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR (2021)
Alex X. Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRR (2021)
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
Evaluating model-based planning and planner amortization for continuous control. CoRR (2021)
Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin A. Riedmiller
Representation Matters: Improving Perception and Exploration for Robotics. ICRA (2021)
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, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRL (2021)
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, Martin A. Riedmiller, S. M. Ali Eslami, Nicolas Heess
Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. CoRL (2021)
Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin A. Riedmiller
Representation Matters: Improving Perception and Exploration for Robotics. CoRR (2020)
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, Martin A. Riedmiller
Local Search for Policy Iteration in Continuous Control. CoRR (2020)
Chris Paxton, Yonatan Bisk, Jesse Thomason, Arunkumar Byravan, Dieter Fox
Prospection: Interpretable plans from language by predicting the future. ICRA (2019)
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. CoRR (2019)
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. CoRL (2019)
Chris Paxton, Yonatan Bisk, Jesse Thomason, Arunkumar Byravan, Dieter Fox
Prospection: Interpretable Plans From Language By Predicting the Future. CoRR (2019)
Felix Leeb, Arunkumar Byravan, Dieter Fox
Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB. CoRR (2019)
Arunkumar Byravan, Felix Leeb, Franziska Meier, Dieter Fox
SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Control. ICRA (2018)
Arunkumar Byravan, Dieter Fox
SE3-nets: Learning rigid body motion using deep neural networks. ICRA (2017)
Arunkumar Byravan, Felix Leeb, Franziska Meier, Dieter Fox
SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control. CoRR (2017)
Arunkumar Byravan, Dieter Fox
SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks. CoRR (2016)
Zita Marinho, Anca D. Dragan, Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Geoffrey J. Gordon
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. CoRR (2016)
Zita Marinho, Byron Boots, Anca D. Dragan, Arunkumar Byravan, Geoffrey J. Gordon, Siddhartha S. Srinivasa
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. Robotics: Science and Systems (2016)
Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox
Graph-Based Inverse Optimal Control for Robot Manipulation. IJCAI (2015)
Byron Boots, Arunkumar Byravan, Dieter Fox
Learning predictive models of a depth camera & manipulator from raw execution traces. ICRA (2014)
Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Dieter Fox
Space-time functional gradient optimization for motion planning. ICRA (2014)