| 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 | 259 | 2023 |
| Backprop kf: Learning discriminative deterministic state estimators T Haarnoja, A Ajay, S Levine, P Abbeel Advances in neural information processing systems 29, 2016 | 236 | 2016 |
| Offline Primitive Discovery for Accelerating Data-Driven Reinforcement Learning A Ajay, A Kumar, P Agrawal, S Levine, O Nachum | 166* | 2021 |
| 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 | 139 | 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 | 59 | 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 | 44 | 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 | 39 | 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 | 35* | 2023 |
| 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 | 27 | 2024 |
| 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 | 27 | 2019 |
| Overcoming the spectral bias of neural value approximation G Yang, A Ajay, P Agrawal arXiv preprint arXiv:2206.04672, 2022 | 20 | 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 | 13 | 2020 |
| Distributionally Adaptive Meta Reinforcement Learning A Ajay, A Gupta, D Ghosh, S Levine, P Agrawal arXiv preprint arXiv:2210.03104, 2022 | 11 | 2022 |
| An introduction to vision-language modeling F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk, O Mañas, Z Lin, ... arXiv preprint arXiv:2405.17247, 2024 | 9 | 2024 |
| Statistical learning under heterogenous distribution shift M Simchowitz, A Ajay, P Agrawal, A Krishnamurthy International Conference on Machine Learning, 31800-31851, 2023 | 5 | 2023 |
| 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 | 2 | 2023 |
| Learning Action Priors for Visuomotor transfer A Ajay, P Agrawal International Conference on Machine Learning workshop on Inductive Biases …, 2020 | 2 | 2020 |
| Learning skill hierarchies from predicate descriptions and self-supervision T Silver, R Chitnis, A Ajay, J Tenenbaum, LP Kaelbling AAAI GenPlan Workshop, 2020 | 2 | 2020 |
| 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 | | 2024 |
| Augmenting physics simulators with neural networks for model learning and control A Ajay Massachusetts Institute of Technology, 2019 | | 2019 |
Joshua B. TenenbaumMIT在 mit.edu 的电子邮件经过验证
