John D. Co-Reyes

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All published works

Action	Title	Year	Authors
+ PDF Chat	Training Language Models to Self-Correct via Reinforcement Learning	2024	Aviral Kumar Vincent Zhuang Rishabh Agarwal Yi Su John D. Co-Reyes Avi Singh Kate Baumli Shariq Iqbal Colton Bishop Rebecca Roelofs
+ PDF Chat	Many-Shot In-Context Learning	2024	Rishabh Agarwal Avi Singh Lei M. Zhang Bernd Bohnet Stephanie C. Y. Chan Ankesh Anand Zaheer Abbas Azade Nova John D. Co-Reyes Eric King‐wah Chu
+ PDF Chat	Guided Evolution with Binary Discriminators for ML Program Search	2024	John D. Co-Reyes Yingjie Miao George Tucker Aleksandra Faust Esteban Real
+	Small-scale proxies for large-scale Transformer training instabilities	2023	Mitchell Wortsman Peter J. Liu Lechao Xiao Katie Everett Alex Alemi Ben Adlam John D. Co-Reyes İzzeddin Gür Abhishek Kumar Roman Novak
+	Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research	2023	Cole Gulino Justin Fu Wenjie Luo George Tucker Eli Bronstein Yiren Lu Jean Harb Xinlei Pan Yan Wang Xiangyu Chen
+	Improving Large Language Model Fine-tuning for Solving Math Problems	2023	Yixin Liu Avi Singh C. Daniel Freeman John D. Co-Reyes Peter J. Liu
+	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models	2023	Avi Singh John D. Co-Reyes Rishabh Agarwal Ankesh Anand Piyush Patil Peter J. Liu J. Harrison Jaehoon Lee Kelvin Xu Aaron Parisi
+	Evolving Pareto-Optimal Actor-Critic Algorithms for Generalizability and Stability	2022	Juan Jose Garau Luis Yingjie Miao John D. Co-Reyes Aaron Parisi Jie Tan Esteban Real Aleksandra Faust
+ PDF Chat	Information is Power: Intrinsic Control via Information Capture	2021	Nicholas Rhinehart Jenny Wang Glen Berseth John D. Co-Reyes Danijar Hafner Chelsea Finn Sergey Levine
+	Evolving Reinforcement Learning Algorithms	2021	John D. Co-Reyes Yingjie Miao Daiyi Peng Esteban Real Sergey Levine Quoc V. Le Honglak Lee Aleksandra Faust
+	Differentiable Architecture Search for Reinforcement Learning	2021	Yingjie Miao Xingyou Song John D. Co-Reyes Daiyi Peng Summer Yue Eugene Brevdo Aleksandra Faust
+	Evolving Reinforcement Learning Algorithms	2021	John D. Co-Reyes Yingjie Miao Daiyi Peng Esteban Real Sergey Levine Quoc V. Le Honglak Lee Aleksandra Faust
+	Information is Power: Intrinsic Control via Information Capture	2021	Nicholas Rhinehart Jenny Wang Glen Berseth John D. Co-Reyes Danijar Hafner Chelsea Finn Sergey Levine
+	Ecological Reinforcement Learning	2020	John D. Co-Reyes Suvansh Sanjeev Glen Berseth Abhishek Gupta Sergey Levine
+	Entity Abstraction in Visual Model-Based Reinforcement Learning	2019	Rishi Veerapaneni John D. Co-Reyes Michael Chang Michael Jänner Chelsea Finn Jiajun Wu Joshua B. Tenenbaum Sergey Levine
+	Entity Abstraction in Visual Model-Based Reinforcement Learning	2019	Rishi Veerapaneni John D. Co-Reyes Michael Chang Michael Jänner Chelsea Finn Jiajun Wu Joshua B. Tenenbaum Sergey Levine
+	Guiding Policies with Language via Meta-Learning	2018	John D. Co-Reyes Abhishek Gupta Suvansh Sanjeev Nick Altieri Jacob Andreas John DeNero Pieter Abbeel Sergey Levine
+	Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings	2018	John D. Co-Reyes YuXuan Liu Abhishek Gupta Benjamin Eysenbach Pieter Abbeel Sergey Levine
+	Guiding Policies with Language via Meta-Learning	2018	John D. Co-Reyes Abhishek Gupta Suvansh Sanjeev Nick Altieri Jacob Andreas John DeNero Pieter Abbeel Sergey Levine
+	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning	2017	Justin Fu John D. Co-Reyes Sergey Levine
+	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning	2017	Justin Fu John D. Co-Reyes Sergey Levine

Common Coauthors

Coauthor	Papers Together
Sergey Levine	12
Aleksandra Faust	8
Yingjie Miao	5
Rishabh Agarwal	4
Abhishek Gupta	4
Avi Singh	4
Chelsea Finn	4
Esteban Real	4
Pieter Abbeel	3
Suvansh Sanjeev	3
Daiyi Peng	3
Justin Fu	3
Glen Berseth	3
George Tucker	3
Jenny Wang	2
İzzeddin Gür	2
Lechao Xiao	2
Jeffrey Pennington	2
Ankesh Anand	2
Ben Adlam	2
Jaehoon Lee	2
Quoc V. Le	2
Peter J. Liu	2
Michael Jänner	2
Danijar Hafner	2
Aaron Parisi	2
Jiajun Wu	2
John DeNero	2
Alex Alemi	2
Nicholas Rhinehart	2
Jacob Andreas	2
Rishi Veerapaneni	2
Rebecca Roelofs	2
Kelvin Xu	2
Nick Altieri	2
Azade Nova	2
Bernd Bohnet	2
Roman Novak	2
Jascha Sohl‐Dickstein	2
Joshua B. Tenenbaum	2
Feryal Behbahani	2
Honglak Lee	2
Benjamin Eysenbach	1
Benjamin Sapp	1
Jie Tan	1
Lei M. Zhang	1
Igor Mordatch	1
Eli Bronstein	1
C. Daniel Freeman	1
Summer Yue	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	VIME: Variational Information Maximizing Exploration	2016	Rein Houthooft Xi Chen Yan Duan John Schulman Filip De Turck Pieter Abbeel	3
+	Curiosity-driven Exploration by Self-supervised Prediction	2017	Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell	2
+	Unifying Count-Based Exploration and Intrinsic Motivation	2016	Marc G. Bellemare Sriram Srinivasan Georg Ostrovski Tom Schaul David Saxton Rémi Munos	2
+	Trust Region Policy Optimization	2015	John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel	2
+ PDF Chat	Representation Learning for Grounded Spatial Reasoning	2018	Michael Jänner Karthik Narasimhan Regina Barzilay	2
+	Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models	2015	Bradly C. Stadie Sergey Levine Pieter Abbeel	2
+	Stochastic Neural Networks for Hierarchical Reinforcement Learning	2017	Carlos Florensa Yan Duan Pieter Abbeel	2
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	2
+	Learning to reinforcement learn	2016	Jane X. Wang Zeb Kurth‐Nelson Dhruva Tirumala Hubert Soyer Joel Z. Leibo Rémi Munos Charles Blundell Dharshan Kumaran Matt Botvinick	2
+	Learning and Transfer of Modulated Locomotor Controllers	2016	Nicolas Heess Gregory Wayne Yuval Tassa Timothy Lillicrap Martin Riedmiller David Silver	2
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	2
+	Understanding Visual Concepts with Continuation Learning	2016	WILLIAM F. WHITNEY Michael Chang Tejas D. Kulkarni Joshua B. Tenenbaum	1
+	Deep reinforcement learning with double Q-Learning	2016	Hado van Hasselt Arthur Guez David Silver	1
+	Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains	2016	David Abel Alekh Agarwal Fernando Díaz Akshay Krishnamurthy Robert E. Schapire	1
+	Deep Exploration via Bootstrapped DQN	2016	Ian Osband Charles Blundell Alexander Pritzel Benjamin Van Roy	1
+	Binding via Reconstruction Clustering	2015	Klaus Greff Rupesh K. Srivastava Jürgen Schmidhuber	1
+	Action-Conditional Video Prediction using Deep Networks in Atari Games	2015	Junhyuk Oh Xiaoxiao Guo Honglak Lee Richard L. Lewis Satinder Singh	1
+ PDF Chat	Alignment-Based Compositional Semantics for Instruction Following	2015	Jacob Andreas Dan Klein	1
+	Concrete Problems in AI Safety	2016	Dario Amodei Chris Olah Jacob Steinhardt Paul F. Christiano John Schulman Dan Mané	1
+	Deep multi-scale video prediction beyond mean square error	2015	Michaël Mathieu Camille Couprie Yann LeCun	1
+	Improved Techniques for Training GANs	2016	Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen	1
+	Tutorial on Variational Autoencoders	2016	Carl Doersch	1
+	The Option-Critic Architecture	2016	Pierre‐Luc Bacon Jean Harb Doina Precup	1
+ PDF Chat	Deep visual foresight for planning robot motion	2017	Chelsea Finn Sergey Levine	1
+	Deep reinforcement learning from human preferences	2017	Paul F. Christiano Jan Leike T. B. Brown Miljan Martic Shane Legg Dario Amodei	1
+	Neural Programmer-Interpreters	2015	Scott Reed Nando de Freitas	1
+	Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning	2017	Joshua Achiam S. Shankar Sastry	1
+	Prediction and Control with Temporal Segment Models	2017	Nikhil Mishra Pieter Abbeel Igor Mordatch	1
+	Prototypical Networks for Few-shot Learning	2017	Jake Snell Kevin Swersky Richard S. Zemel	1
+	Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play	2017	Sainbayar Sukhbaatar Zeming Lin Ilya Kostrikov Gabriel Synnaeve Arthur Szlam Rob Fergus	1
+ PDF Chat	Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation	2014	Ross Girshick Jeff Donahue Trevor Darrell Jitendra Malik	1
+	Continual Learning with Deep Generative Replay	2017	Hanul Shin Jung Kwon Lee Jaehong Kim Jiwon Kim	1
+	Metacontrol for Adaptive Imagination-Based Optimization	2017	Jessica B. Hamrick Andrew J. Ballard Razvan Pascanu Oriol Vinyals Nicolas Heess Peter Battaglia	1
+	Understanding the exploding gradient problem	2012	Razvan Pascanu Tomáš Mikolov Yoshua Bengio	1
+	Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning	2015	Shakir Mohamed Danilo Jimenez Rezende	1
+	Equivalence Between Policy Gradients and Soft Q-Learning	2017	John Schulman Xi Chen Pieter Abbeel	1
+	Benchmarking Deep Reinforcement Learning for Continuous Control	2016	Yan Duan Xi Chen Rein Houthooft John Schulman Pieter Abbeel	1
+	Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics	2017	Ken Kansky Tom Silver David A. Mély Mohamed Eldawy Miguel Lázaro-Gredilla Xinghua Lou Nimrod Dorfman Szymon Sidor Scott Phoenix Dileep George	1
+	Reset-free Trial-and-Error Learning for Robot Damage Recovery	2017	Konstantinos Chatzilygeroudis Vassilis Vassiliades Jean-Baptiste Mouret	1
+	Emergence of Locomotion Behaviours in Rich Environments	2017	Nicolas Heess Dhruva Tb Sriram Srinivasan Jay Lemmon Josh Merel Greg Wayne Yuval Tassa Tom Erez Ziyu Wang S. M. Ali Eslami	1
+	Learning to Learn: Meta-Critic Networks for Sample Efficient Learning	2017	Flood Sung Zhang Li Tao Xiang Timothy M. Hospedales Yongxin Yang	1
+	Meta-Learning with Temporal Convolutions.	2017	Nikhil Mishra Mostafa Rohaninejad Xi Chen Pieter Abbeel	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation	2016	Tejas D. Kulkarni Karthik Narasimhan Ardavan Saeedi Joshua B. Tenenbaum	1
+	Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces	2017	Garrett Warnell Nicholas R. Waytowich Vernon J. Lawhern Peter Stone	1
+	Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments	2017	Maruan Al-Shedivat Trapit Bansal Yuri Burda Ilya Sutskever Igor Mordatch Pieter Abbeel	1
+	Meta Learning Shared Hierarchies	2017	Kevin Frans Jonathan Ho Xi Chen Pieter Abbeel John Schulman	1
+	Primal-Dual $π$ Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems	2017	Mengdi Wang	1
+	Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm	2017	Chelsea Finn Sergey Levine	1
+	Continuous control with deep reinforcement learning	2015	Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel Nicolas Heess Tom Erez Yuval Tassa David Silver Daan Wierstra	1