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ORCIDAnurag Ajay
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2020 – today
- 2024
[c14]Arjun Majumdar, Anurag Ajay, Xiaohan Zhang, Pranav Putta, Sriram Yenamandra, Mikael Henaff, Sneha Silwal, Paul McVay, Oleksandr Maksymets, Sergio Arnaud, Karmesh Yadav, Qiyang Li, Ben Newman, Mohit Sharma, Vincent-Pierre Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan, Franziska Meier, Chris Paxton, Alexander Sax, Aravind Rajeswaran:
OpenEQA: Embodied Question Answering in the Era of Foundation Models. CVPR 2024: 16488-16498- [i15]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i14]Zechu Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki:
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. CoRR abs/2406.00681 (2024) - 2023
- [j2]Anurag Ajay
, Madhulika Singh, Subhajit Patra, Harshit Ranjan, Ajay Pundir, Shishpal Poonia, Anurag Kumar, Deepak K. Singh, Pankaj Kumar, Moben Ignatius, Prabhat Kumar, Sonam R. Sherpa, Ram K. Malik, Virender Kumar, Sudhanshu Singh, Peter Craufurd, Andrew J. McDonald:
Multi-Year On-Farm Trial Data on the Performance of Long- and Short-Duration Wheat Varieties against Sowing Dates in the Eastern Indo-Gangetic Plain of India. Data 8(2): 39 (2023) - [c13]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision Making? ICLR 2023 - [c12]Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal:
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. ICML 2023: 19440-19459 - [c11]Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy:
Statistical Learning under Heterogenous Distribution Shift. ICML 2023: 31800-31851 - [c10]Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal:
Compositional Foundation Models for Hierarchical Planning. NeurIPS 2023 - [i13]Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy:
Statistical Learning under Heterogenous Distribution Shift. CoRR abs/2302.13934 (2023) - [i12]Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal:
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. CoRR abs/2307.12983 (2023) - [i11]Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Josh Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal:
Compositional Foundation Models for Hierarchical Planning. CoRR abs/2309.08587 (2023) - 2022
- [c9]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming The Spectral Bias of Neural Value Approximation. ICLR 2022 - [c8]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should Be Trained to be Adaptive. ICML 2022: 7513-7530 - [c7]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS 2022 - [i10]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming the Spectral Bias of Neural Value Approximation. CoRR abs/2206.04672 (2022) - [i9]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should be Trained to be Adaptive. CoRR abs/2207.02200 (2022) - [i8]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - [i7]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision-Making? CoRR abs/2211.15657 (2022) - 2021
- [c6]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR 2021 - 2020
- [c5]Nima Fazeli, Anurag Ajay, Alberto Rodriguez:
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners. ICRA 2020: 7898-7904 - [i6]Nima Fazeli, Anurag Ajay, Alberto Rodriguez:
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners. CoRR abs/2009.03994 (2020) - [i5]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR abs/2010.13611 (2020)
2010 – 2019
- 2019
- [j1]Mehmet Turan, Yasin Almalioglu, Hunter B. Gilbert, Faisal Mahmood, Nicholas J. Durr, Helder Araújo, Alp Eren Sari, Anurag Ajay, Metin Sitti:
Learning to Navigate Endoscopic Capsule Robots. IEEE Robotics Autom. Lett. 4(3): 3075-3082 (2019) - [c4]Anurag Ajay, Maria Bauzá, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie Pack Kaelbling:
Combining Physical Simulators and Object-Based Networks for Control. ICRA 2019: 3217-3223 - [i4]Anurag Ajay, Maria Bauzá, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie Pack Kaelbling:
Combining Physical Simulators and Object-Based Networks for Control. CoRR abs/1904.06580 (2019) - 2018
- [c3]Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauzá, Leslie Pack Kaelbling, Joshua B. Tenenbaum, Alberto Rodriguez:
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing. IROS 2018: 3066-3073 - [i3]Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauzá, Leslie Pack Kaelbling, Joshua B. Tenenbaum, Alberto Rodriguez:
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing. CoRR abs/1808.03246 (2018) - 2017
- [c2]William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine:
Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states. ICRA 2017: 3373-3380 - 2016
- [c1]Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel:
Backprop KF: Learning Discriminative Deterministic State Estimators. NIPS 2016: 4376-4384 - [i2]Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel:
Backprop KF: Learning Discriminative Deterministic State Estimators. CoRR abs/1605.07148 (2016) - [i1]William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine:
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States. CoRR abs/1610.01112 (2016)
Coauthor Index
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