| Decision transformer: Reinforcement learning via sequence modeling L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ... Advances in Neural Information Processing Systems 2021, 2021 | 2621 | 2021 |
| Data-Efficient Image Recognition with Contrastive Predictive Coding OJ Hénaff, A Srinivas, J De Fauw, A Razavi, C Doersch, SMA Eslami, ... International Conference on Machine Learning, 2020, 2019 | 1825 | 2019 |
| Bottleneck transformers for visual recognition A Srinivas, TY Lin, N Parmar, J Shlens, P Abbeel, A Vaswani Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 1637 | 2021 |
| Simple copy-paste is a strong data augmentation method for instance segmentation G Ghiasi*, Y Cui*, A Srinivas*, R Qian, TY Lin, ED Cubuk, QV Le, B Zoph Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 1535 | 2021 |
| Curl: Contrastive unsupervised representations for reinforcement learning A Srinivas, M Laskin, P Abbeel International Conference on Machine Learning, 2020, 2020 | 1480 | 2020 |
| Reinforcement Learning with Augmented Data M Laskin, K Lee, A Stooke, L Pinto, P Abbeel, A Srinivas Advances in Neural Information Processing Systems 2020, 2020 | 958 | 2020 |
| Videogpt: Video generation using vq-vae and transformers W Yan, Y Zhang, P Abbeel, A Srinivas arXiv preprint arXiv:2104.10157, 2021 | 741 | 2021 |
| Scaling local self-attention for parameter efficient visual backbones A Vaswani, P Ramachandran, A Srinivas, N Parmar, B Hechtman, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 600 | 2021 |
| Flow++: Improving flow-based generative models with variational dequantization and architecture design J Ho, X Chen, A Srinivas, Y Duan, P Abbeel International Conference on Machine Learning, 2019, 2019 | 599 | 2019 |
| Revisiting resnets: Improved training and scaling strategies I Bello, W Fedus, X Du, ED Cubuk, A Srinivas, TY Lin, J Shlens, B Zoph Advances in Neural Information Processing Systems 2021, 2021 | 456 | 2021 |
| Universal planning networks: Learning generalizable representations for visuomotor control A Srinivas, A Jabri, P Abbeel, S Levine, C Finn International Conference on Machine Learning, 2018, 2018 | 336 | 2018 |
| Learning to repeat: Fine grained action repetition for deep reinforcement learning S Sharma, A Srinivas, B Ravindran arXiv preprint arXiv:1702.06054, 2017 | 156 | 2017 |
| Dynamic action repetition for deep reinforcement learning A Srinivas, S Sharma, B Ravindran Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 107* | 2017 |
| Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain A Srinivas, J Rajendran, MM Khapra, P P, B Ravindran International Conference on Learning Representations, 2017, 2017 | 96* | 2017 |
| Selfaugment: Automatic augmentation policies for self-supervised learning CJ Reed, S Metzger, A Srinivas, T Darrell, K Keutzer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 86* | 2021 |
