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Shikhar Bahl
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Conference and Workshop Papers
- 2023
- [c16]Aditya Kannan, Kenneth Shaw, Shikhar Bahl, Pragna Mannam, Deepak Pathak:
DEFT: Dexterous Fine-Tuning for Hand Policies. CoRL 2023: 928-942 - [c15]Lili Chen, Shikhar Bahl, Deepak Pathak:
PlayFusion: Skill Acquisition via Diffusion from Language-Annotated Play. CoRL 2023: 2012-2029 - [c14]Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain, Deepak Pathak:
Affordances from Human Videos as a Versatile Representation for Robotics. CVPR 2023: 1-13 - [c13]Kevin Gmelin, Shikhar Bahl, Russell Mendonca, Deepak Pathak:
Efficient RL via Disentangled Environment and Agent Representations. ICML 2023: 11525-11545 - [c12]Russell Mendonca, Shikhar Bahl, Deepak Pathak:
ALAN: Autonomously Exploring Robotic Agents in the Real World. ICRA 2023: 3044-3050 - [c11]Russell Mendonca, Shikhar Bahl, Deepak Pathak:
Structured World Models from Human Videos. Robotics: Science and Systems 2023 - 2022
- [c10]Kenneth Shaw, Shikhar Bahl, Deepak Pathak:
VideoDex: Learning Dexterity from Internet Videos. CoRL 2022: 654-665 - [c9]Shikhar Bahl, Abhinav Gupta, Deepak Pathak:
Human-to-Robot Imitation in the Wild. Robotics: Science and Systems 2022 - 2021
- [c8]Sudeep Dasari, Jianren Wang, Joyce Hong, Shikhar Bahl, Yixin Lin, Austin S. Wang, Abitha Thankaraj, Karanbir Chahal, Berk Çalli, Saurabh Gupta, David Held, Lerrel Pinto, Deepak Pathak, Vikash Kumar, Abhinav Gupta:
RB2: Robotic Manipulation Benchmarking with a Twist. NeurIPS Datasets and Benchmarks 2021 - [c7]Shikhar Bahl, Abhinav Gupta, Deepak Pathak:
Hierarchical Neural Dynamic Policies. Robotics: Science and Systems 2021 - 2020
- [c6]Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine:
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning. ICML 2020: 7783-7792 - [c5]Gerrit Schoettler, Ashvin Nair, Jianlan Luo, Shikhar Bahl, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine:
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards. IROS 2020: 5548-5555 - [c4]Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta, Deepak Pathak:
Neural Dynamic Policies for End-to-End Sensorimotor Learning. NeurIPS 2020 - 2019
- [c3]Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine:
Contextual Imagined Goals for Self-Supervised Robotic Learning. CoRL 2019: 530-539 - [c2]Tobias Johannink, Shikhar Bahl, Ashvin Nair, Jianlan Luo, Avinash Kumar, Matthias Loskyll, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine:
Residual Reinforcement Learning for Robot Control. ICRA 2019: 6023-6029 - 2018
- [c1]Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine:
Visual Reinforcement Learning with Imagined Goals. NeurIPS 2018: 9209-9220
Informal and Other Publications
- 2023
- [i16]Russell Mendonca, Shikhar Bahl, Deepak Pathak:
ALAN: Autonomously Exploring Robotic Agents in the Real World. CoRR abs/2302.06604 (2023) - [i15]Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain, Deepak Pathak:
Affordances from Human Videos as a Versatile Representation for Robotics. CoRR abs/2304.08488 (2023) - [i14]Russell Mendonca, Shikhar Bahl, Deepak Pathak:
Structured World Models from Human Videos. CoRR abs/2308.10901 (2023) - [i13]Kevin Gmelin, Shikhar Bahl, Russell Mendonca, Deepak Pathak:
Efficient RL via Disentangled Environment and Agent Representations. CoRR abs/2309.02435 (2023) - [i12]Aditya Kannan, Kenneth Shaw, Shikhar Bahl, Pragna Mannam, Deepak Pathak:
DEFT: Dexterous Fine-Tuning for Real-World Hand Policies. CoRR abs/2310.19797 (2023) - [i11]Lili Chen, Shikhar Bahl, Deepak Pathak:
PlayFusion: Skill Acquisition via Diffusion from Language-Annotated Play. CoRR abs/2312.04549 (2023) - 2022
- [i10]Sudeep Dasari, Jianren Wang, Joyce Hong, Shikhar Bahl, Yixin Lin, Austin S. Wang, Abitha Thankaraj, Karanbir Chahal, Berk Çalli, Saurabh Gupta, David Held, Lerrel Pinto, Deepak Pathak, Vikash Kumar, Abhinav Gupta:
RB2: Robotic Manipulation Benchmarking with a Twist. CoRR abs/2203.08098 (2022) - [i9]Shikhar Bahl, Abhinav Gupta, Deepak Pathak:
Human-to-Robot Imitation in the Wild. CoRR abs/2207.09450 (2022) - [i8]Kenneth Shaw, Shikhar Bahl, Deepak Pathak:
VideoDex: Learning Dexterity from Internet Videos. CoRR abs/2212.04498 (2022) - 2021
- [i7]Shikhar Bahl, Abhinav Gupta, Deepak Pathak:
Hierarchical Neural Dynamic Policies. CoRR abs/2107.05627 (2021) - 2020
- [i6]Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta, Deepak Pathak:
Neural Dynamic Policies for End-to-End Sensorimotor Learning. CoRR abs/2012.02788 (2020) - 2019
- [i5]Vitchyr H. Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine:
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning. CoRR abs/1903.03698 (2019) - [i4]Gerrit Schoettler, Ashvin Nair, Jianlan Luo, Shikhar Bahl, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine:
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards. CoRR abs/1906.05841 (2019) - [i3]Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine:
Contextual Imagined Goals for Self-Supervised Robotic Learning. CoRR abs/1910.11670 (2019) - 2018
- [i2]Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine:
Visual Reinforcement Learning with Imagined Goals. CoRR abs/1807.04742 (2018) - [i1]Tobias Johannink, Shikhar Bahl, Ashvin Nair, Jianlan Luo, Avinash Kumar, Matthias Loskyll, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine:
Residual Reinforcement Learning for Robot Control. CoRR abs/1812.03201 (2018)
Coauthor Index
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