Aravind Srinivas

According to our database, Aravind Srinivas authored at least 18 papers between 2018 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

VideoGPT: Video Generation using VQ-VAE and Transformers.

Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas

CoRR, 2021

Reinforcement Learning with Latent Flow.

Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings.

Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Decision Transformer: Reinforcement Learning via Sequence Modeling.

Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting ResNets: Improved Training and Scaling Strategies.

Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning.

Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel

Proceedings of the 38th International Conference on Machine Learning, 2021

Scaling Local Self-Attention for Parameter Efficient Visual Backbones.

Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Bottleneck Transformers for Visual Recognition.

Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning.

Colorado J. Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation.

Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

D2RL: Deep Dense Architectures in Reinforcement Learning.

Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg

CoRR, 2020

Evaluating Self-Supervised Pretraining Without Using Labels.

Colorado Reed, Sean Metzger, Aravind Srinivas, Trevor Darrell, Kurt Keutzer

CoRR, 2020

Reinforcement Learning with Augmented Data.

Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CURL: Contrastive Unsupervised Representations for Reinforcement Learning.

Michael Laskin, Aravind Srinivas, Pieter Abbeel

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Data-Efficient Image Recognition with Contrastive Predictive Coding.

Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord

CoRR, 2019

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design.

Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Universal Planning Networks.

Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn

CoRR, 2018

Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control.

Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, Chelsea Finn

Proceedings of the 35th International Conference on Machine Learning, 2018