Anurag Ajay

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 30

Top Topics

Policy Gradient

Term Weighting Schemes

Top Venues

Publications

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 (2024)
Zechu Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. CoRR (2024)
Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy
Statistical Learning under Heterogenous Distribution Shift. CoRR (2023)
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)
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)
Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy
Statistical Learning under Heterogenous Distribution Shift. ICML (2023)
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 (2023)
Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. CoRR (2023)
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) (2023)
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)
Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
Offline RL Policies Should be Trained to be Adaptive. CoRR (2022)
Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Distributionally Adaptive Meta Reinforcement Learning. CoRR (2022)
Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
Offline RL Policies Should Be Trained to be Adaptive. ICML (2022)
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 (2022)
Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS (2022)
Ge Yang, Anurag Ajay, Pulkit Agrawal
Overcoming The Spectral Bias of Neural Value Approximation. ICLR (2022)
Ge Yang, Anurag Ajay, Pulkit Agrawal
Overcoming the Spectral Bias of Neural Value Approximation. CoRR (2022)
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR (2021)
Nima Fazeli, Anurag Ajay, Alberto Rodriguez
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners. ICRA (2020)
Nima Fazeli, Anurag Ajay, Alberto Rodriguez
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners. CoRR (2020)
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR (2020)
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) (2019)
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 (2019)
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)
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 (2018)
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)
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)
William Montgomery, Anurag Ajay, Chelsea Finn, Pieter Abbeel, Sergey Levine
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States. CoRR (2016)
Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel
Backprop KF: Learning Discriminative Deterministic State Estimators. NIPS (2016)
Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel
Backprop KF: Learning Discriminative Deterministic State Estimators. CoRR (2016)