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 | 1637 | 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 | 1632 | 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 | 1296 | 2021 |
Curl: Contrastive unsupervised representations for reinforcement learning A Srinivas, M Laskin, P Abbeel International Conference on Machine Learning, 2020, 2020 | 1171 | 2020 |
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 | 1126 | 2021 |
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 | 759 | 2020 |
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 | 510 | 2019 |
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 | 481 | 2021 |
Videogpt: Video generation using vq-vae and transformers W Yan, Y Zhang, P Abbeel, A Srinivas arXiv preprint arXiv:2104.10157, 2021 | 413 | 2021 |
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 | 358 | 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 | 313 | 2018 |
Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning K Lee, M Laskin, A Srinivas, P Abbeel International Conference on Machine Learning, 6131-6141, 2021 | 251 | 2021 |
Learning to repeat: Fine grained action repetition for deep reinforcement learning S Sharma, A Srinivas, B Ravindran arXiv preprint arXiv:1702.06054, 2017 | 130 | 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 | 105* | 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 | 83* | 2017 |
D2rl: Deep dense architectures in reinforcement learning S Sinha, H Bharadhwaj, A Srinivas, A Garg arXiv preprint arXiv:2010.09163, 2020 | 76 | 2020 |
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 | 75* | 2021 |
Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering A Srinivas, R Krishnamurthy, P Kumar, B Ravindran arXiv preprint arXiv:1605.05359, 2016 | 50 | 2016 |
Making the most of our regrets: Regret-based solutions to handle payoff uncertainty and elicitation in green security games TH Nguyen, FM Delle Fave, D Kar, A Srinivas, A Yadav, M Tambe, ... International Conference on Decision and Game Theory for Security, 170-191, 2015 | 46 | 2015 |
Reinforcement learning with few expert demonstrations A Srinivas, S Ozair, Y Bengio NIPS Workshop on Deep Learning for Action and Interaction 2016, 2016 | 30* | 2016 |