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
Is Conditional Generative Modeling all you need for Decision Making?
A Ajay, Y Du, A Gupta, J Tenenbaum, T Jaakkola, P Agrawal
International Conference on Learning Representations (ICLR), 𝐍𝐨𝐭𝐚𝐛𝐥𝐞-𝐭𝐨𝐩-𝟓%, 2023
Offline Primitive Discovery for Accelerating Data-Driven Reinforcement Learning
A Ajay, A Kumar, P Agrawal, S Levine, O Nachum
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
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
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
Compositional Foundation Models for Hierarchical Planning
A Ajay, S Han, Y Du, S Li, A Gupta, T Jaakkola, J Tenenbaum, L Kaelbling, ...
arXiv preprint arXiv:2309.08587, 2023
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
Overcoming the spectral bias of neural value approximation
G Yang, A Ajay, P Agrawal
arXiv preprint arXiv:2206.04672, 2022
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
Distributionally Adaptive Meta Reinforcement Learning
A Ajay, A Gupta, D Ghosh, S Levine, P Agrawal
arXiv preprint arXiv:2210.03104, 2022
Openeqa: Embodied question answering in the era of foundation models
A Majumdar, A Ajay, X Zhang, P Putta, S Yenamandra, M Henaff, S Silwal, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Statistical learning under heterogenous distribution shift
M Simchowitz, A Ajay, P Agrawal, A Krishnamurthy
International Conference on Machine Learning, 31800-31851, 2023
Learning skill hierarchies from predicate descriptions and self-supervision
T Silver, R Chitnis, A Ajay, J Tenenbaum, LP Kaelbling
AAAI GenPlan Workshop, 2020
Parallel -Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
Z Li, T Chen, ZW Hong, A Ajay, P Agrawal
International Conference on Machine Learning, 19440-19459, 2023
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
Z Li, R Krohn, T Chen, A Ajay, P Agrawal, G Chalvatzaki
arXiv preprint arXiv:2406.00681, 2024
An Introduction to Vision-Language Modeling
F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk, O Maņas, Z Lin, ...
arXiv preprint arXiv:2405.17247, 2024
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
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