Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control. - Aravind Srinivas; Allan Jabri; Pieter Abbeel; Sergey Levine; Chelsea Finn (ICML, 2018)

Universal Planning Networks. - Aravind Srinivas; Allan Jabri; Pieter Abbeel; Sergey Levine; Chelsea Finn (CoRR, 2018)

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. - Jonathan Ho; Xi Chen 022; Aravind Srinivas; Yan Duan; Pieter Abbeel (ICML, 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)

CURL: Contrastive Unsupervised Representations for Reinforcement Learning. - Michael Laskin; Aravind Srinivas; Pieter Abbeel (ICML, 2020)

Reinforcement Learning with Augmented Data. - Michael Laskin; Kimin Lee; Adam Stooke; Lerrel Pinto; Pieter Abbeel; Aravind Srinivas (NeurIPS, 2020)

Evaluating Self-Supervised Pretraining Without Using Labels. - Colorado Reed; Sean Metzger; Aravind Srinivas; Trevor Darrell; Kurt Keutzer (CoRR, 2020)

D2RL: Deep Dense Architectures in Reinforcement Learning. - Samarth Sinha; Homanga Bharadhwaj; Aravind Srinivas; Animesh Garg (CoRR, 2020)

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 (CVPR, 2021)

SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning. - Colorado J. Reed; Sean Metzger; Aravind Srinivas; Trevor Darrell; Kurt Keutzer (CVPR, 2021)

Bottleneck Transformers for Visual Recognition. - Aravind Srinivas; Tsung-Yi Lin; Niki Parmar; Jonathon Shlens; Pieter Abbeel; Ashish Vaswani (CVPR, 2021)

Scaling Local Self-Attention for Parameter Efficient Visual Backbones. - Ashish Vaswani; Prajit Ramachandran; Aravind Srinivas; Niki Parmar; Blake A. Hechtman; Jonathon Shlens (CVPR, 2021)

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. - Kimin Lee; Michael Laskin; Aravind Srinivas; Pieter Abbeel (ICML, 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 (NeurIPS, 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 (NeurIPS, 2021)

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. - Lili Chen; Kimin Lee; Aravind Srinivas; Pieter Abbeel (NeurIPS, 2021)

Reinforcement Learning with Latent Flow. - Wenling Shang; Xiaofei Wang 008; Aravind Srinivas; Aravind Rajeswaran; Yang Gao 029; Pieter Abbeel; Michael Laskin (NeurIPS, 2021)

VideoGPT: Video Generation using VQ-VAE and Transformers. - Wilson Yan; Yunzhi Zhang; Pieter Abbeel; Aravind Srinivas (CoRR, 2021)