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Aravind Srinivas
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2020 – today
- 2021
- [c13]Colorado J. Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer:
SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning. CVPR 2021: 2674-2683 - [c12]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation. CVPR 2021: 2918-2928 - [c11]Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens:
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CVPR 2021: 12894-12904 - [c10]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CVPR 2021: 16519-16529 - [c9]Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel:
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. ICML 2021: 6131-6141 - [c8]Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS 2021: 15084-15097 - [c7]Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin:
Reinforcement Learning with Latent Flow. NeurIPS 2021: 22171-22183 - [c6]Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. NeurIPS 2021: 22614-22627 - [c5]Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel:
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. NeurIPS 2021: 26779-26791 - [i16]Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin:
Reinforcement Learning with Latent Flow. CoRR abs/2101.01857 (2021) - [i15]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CoRR abs/2101.11605 (2021) - [i14]Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel:
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. CoRR abs/2103.02886 (2021) - [i13]Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. CoRR abs/2103.07579 (2021) - [i12]Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens:
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CoRR abs/2103.12731 (2021) - [i11]Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas:
VideoGPT: Video Generation using VQ-VAE and Transformers. CoRR abs/2104.10157 (2021) - [i10]Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR abs/2106.01345 (2021) - 2020
- [c4]Michael Laskin, Aravind Srinivas, Pieter Abbeel:
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. ICML 2020: 5639-5650 - [c3]Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas:
Reinforcement Learning with Augmented Data. NeurIPS 2020 - [i9]Aravind Srinivas, Michael Laskin, Pieter Abbeel:
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CoRR abs/2004.04136 (2020) - [i8]Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas:
Reinforcement Learning with Augmented Data. CoRR abs/2004.14990 (2020) - [i7]Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel:
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. CoRR abs/2007.04938 (2020) - [i6]Colorado Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer:
Evaluating Self-Supervised Pretraining Without Using Labels. CoRR abs/2009.07724 (2020) - [i5]Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg:
D2RL: Deep Dense Architectures in Reinforcement Learning. CoRR abs/2010.09163 (2020) - [i4]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation. CoRR abs/2012.07177 (2020)
2010 – 2019
- 2019
- [c2]Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel:
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. ICML 2019: 2722-2730 - [i3]Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel:
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. CoRR abs/1902.00275 (2019) - [i2]Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord:
Data-Efficient Image Recognition with Contrastive Predictive Coding. CoRR abs/1905.09272 (2019) - 2018
- [c1]Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. ICML 2018: 4739-4748 - [i1]Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn:
Universal Planning Networks. CoRR abs/1804.00645 (2018)
Coauthor Index
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