Anurag Ajay
Anurag Ajay
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Backprop kf: Learning discriminative deterministic state estimators
T Haarnoja, A Ajay, S Levine, P Abbeel
Advances in neural information processing systems 29, 2016
Augmenting physical simulators with stochastic neural networks: Case study of planar pushing and bouncing
A Ajay, J Wu, N Fazeli, M Bauza, LP Kaelbling, JB Tenenbaum, ...
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
Offline Primitive Discovery for Accelerating Data-Driven Reinforcement Learning
A Ajay, A Kumar, P Agrawal, S Levine, O Nachum
Combining physical simulators and object-based networks for control
A Ajay, M Bauza, J Wu, N Fazeli, JB Tenenbaum, A Rodriguez, ...
2019 International Conference on Robotics and Automation (ICRA), 3217-3223, 2019
Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states
W Montgomery, A Ajay, C Finn, P Abbeel, S Levine
2017 IEEE International Conference on Robotics and Automation (ICRA), 3373-3380, 2017
Learning to navigate endoscopic capsule robots
M Turan, Y Almalioglu, HB Gilbert, F Mahmood, NJ Durr, H Araujo, ...
IEEE Robotics and Automation Letters 4 (3), 3075-3082, 2019
Long-horizon prediction and uncertainty propagation with residual point contact learners
N Fazeli, A Ajay, A Rodriguez
2020 IEEE International Conference on Robotics and Automation (ICRA), 7898-7904, 2020
Overcoming the spectral bias of neural value approximation
G Yang, A Ajay, P Agrawal
arXiv preprint arXiv:2206.04672, 2022
Offline RL Policies Should be Trained to be Adaptive
D Ghosh, A Ajay, P Agrawal, S Levine
International Conference on Machine Learning, 7513-7530, 2022
Understanding the Generalization Gap in Visual Reinforcement Learning
A Ajay, G Yang, O Nachum, P Agrawal
Augmenting physics simulators with neural networks for model learning and control
A Ajay
Massachusetts Institute of Technology, 2019
Distributionally Adaptive Meta Reinforcement Learning
A Ajay, D Ghosh, S Levine, P Agrawal, A Gupta
Decision Awareness in Reinforcement Learning Workshop at ICML 2022, 0
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Articles 1–12