Byravan, Arunkumar

11 publications

ICML 2025 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, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski

ICLRW 2025 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, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski

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

CoRL 2024 Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin Riedmiller, Nicolas Heess

L4DC 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 Riedmiller, Jonas Buchli

ICLRW 2023 Towards a Unified Agent with Foundation Models Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin Riedmiller

ICLR 2022 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 Riedmiller

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, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin Riedmiller, Raia Hadsell, Francesco Nori

CoRL 2021 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, Martin Riedmiller, S. M. Ali Eslami, Nicolas Heess

CoRL 2019 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 Siegel, Nicolas Heess, Martin Riedmiller

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