| 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 | 263 | 2019 |
| Universal planning networks A Srinivas, A Jabri, P Abbeel, S Levine, C Finn International Conference on Machine Learning, 2018, 2018 | 120 | 2018 |
| 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 | 97 | 2019 |
| Curl: Contrastive unsupervised representations for reinforcement learning A Srinivas, M Laskin, P Abbeel International Conference on Machine Learning, 2020, 2020 | 68 | 2020 |
| 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 | 44 | 2015 |
| Learning to repeat: Fine grained action repetition for deep reinforcement learning S Sharma, A Srinivas, B Ravindran ICLR 2017, 2017 | 41 | 2017 |
| Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain J Rajendran, A Srinivas, MM Khapra, P P, B Ravindran ICLR 2017, 2017 | 36* | 2017 |
| 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 | 35 | 2020 |
| Dynamic frame skip deep q network A Srinivas, S Sharma, B Ravindran Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. 2017, 2016 | 31* | 2016 |
| Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering A Srinivas, R Krishnamurthy, P Kumar, B Ravindran arXiv preprint arXiv:1605.05359, 2016 | 28 | 2016 |
| Reinforcement learning with few expert demonstrations A Srinivas, S Ozair, Y Bengio NIPS Workshop on Deep Learning for Action and Interaction 2016, 2016 | 17* | 2016 |
| Dynamic frame skip deep q network A Srinivas, S Sharma, B Ravindran arXiv preprint arXiv:1605.05365, 2016 | 13* | 2016 |
| Simultaneous influencing and mapping social networks L Soriano Marcolino, A Srinivas, A Yadav, M Tambe International Foundation for Autonomous Agents and Multiagent Systems, 2016 | 5 | 2016 |
| Dynamic action repetition for deep reinforcement learning A Srinivas, S Sharma, B Ravindran Proc. AAAI, 2017 | 4 | 2017 |
| Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning K Lee, M Laskin, A Srinivas, P Abbeel arXiv preprint arXiv:2007.04938, 2020 | 2 | 2020 |
| D2RL: Deep Dense Architectures in Reinforcement Learning S Sinha, H Bharadhwaj, A Srinivas, A Garg arXiv preprint arXiv:2010.09163, 2020 | 1 | 2020 |
| Every team deserves a second chance: an extended study on predicting team performance LS Marcolino, A Srinivas, V Nagarajan, M Tambe Autonomous Agents and Multi-Agent Systems 31 (5), 1003-1054, 2017 | 1 | 2017 |
| Reinforcement Learning with Latent Flow W Shang, X Wang, A Srinivas, A Rajeswaran, Y Gao, P Abbeel, M Laskin arXiv preprint arXiv:2101.01857, 2021 | | 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 arXiv preprint arXiv:2012.07177, 2020 | | 2020 |
| Evaluating Self-Supervised Pretraining Without Using Labels S Metzger, A Srinivas, T Darrell, K Keutzer arXiv preprint arXiv:2009.07724, 2020 | | 2020 |
Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
