Aravind Srinivas

Publication Activity (10 Years)

Years Active: 2018-2021
Publications (10 Years): 29

Top Topics

Image Recognition

Reinforcement Learning

Manually Labeled

Unified Framework

Top Venues

Publications

Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. NeurIPS (2021)
Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
Reinforcement Learning with Latent Flow. NeurIPS (2021)
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani
Bottleneck Transformers for Visual Recognition. CVPR (2021)
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CVPR (2021)
Colorado J. Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer
SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning. CVPR (2021)
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)
Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas
VideoGPT: Video Generation using VQ-VAE and Transformers. CoRR (2021)
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani
Bottleneck Transformers for Visual Recognition. CoRR (2021)
Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. CoRR (2021)
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 (2021)
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 (2021)
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)
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)
Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
Reinforcement Learning with Latent Flow. CoRR (2021)
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. ICML (2021)
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CoRR (2021)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. CoRR (2020)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. NeurIPS (2020)
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. CoRR (2020)
Aravind Srinivas, Michael Laskin, Pieter Abbeel
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CoRR (2020)
Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg
D2RL: Deep Dense Architectures in Reinforcement Learning. CoRR (2020)
Michael Laskin, Aravind Srinivas, Pieter Abbeel
CURL: Contrastive Unsupervised Representations for Reinforcement Learning. ICML (2020)
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 (2020)
Colorado Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer
Evaluating Self-Supervised Pretraining Without Using Labels. CoRR (2020)
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 (2019)
Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. CoRR (2019)
Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. ICML (2019)
Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. ICML (2018)
Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn
Universal Planning Networks. CoRR (2018)