Allan Zhou

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All published works

Action	Title	Year	Authors
+ PDF Chat	Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws	2024	Yiding Jiang Allan Zhou Zhili Feng Sadhika Malladi J. Zico Kolter
+	AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data	2024	Caroline Choi Yoonho Lee Annie Chen Allan Zhou Aditi Raghunathan Chelsea Finn
+ PDF Chat	NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis	2023	Allan Zhou Moo Jin Kim Lirui Wang Pete Florence Chelsea Finn
+	NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis	2023	Allan Zhou Moo Jin Kim Lirui Wang Pete Florence Chelsea Finn
+	Permutation Equivariant Neural Functionals	2023	Allan Zhou Kaien Yang Kaylee Burns Yiding Jiang Samuel Sokota J. Zico Kolter Chelsea Finn
+	Neural Functional Transformers	2023	Allan Zhou Kaien Yang Yiding Jiang Kaylee Burns Winnie Xu Samuel Sokota J. Zico Kolter Chelsea Finn
+	Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback	2023	Katherine Tian Eric Mitchell Allan Zhou Archit Sharma Rafael Rafailov Huaxiu Yao Chelsea Finn Christopher D. Manning
+	Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning	2023	Evan Zheran Liu Sahaana Suri Tong Mu Allan Zhou Chelsea Finn
+	Neural Processing of Tri-Plane Hybrid Neural Fields	2023	Adriano Cardace Pierluigi Zama Ramirez Francesco Ballerini Allan Zhou Samuele Salti Luigi Di Stefano
+	Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use	2023	Lirui Wang Kaiqing Zhang Allan Zhou Max Simchowitz Russ Tedrake
+ PDF Chat	Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback	2023	Katherine Tian Eric Mitchell Allan Zhou Archit Sharma Rafael Rafailov Huaxiu Yao Chelsea Finn Christopher D. Manning
+	Policy Architectures for Compositional Generalization in Control	2022	Allan Zhou Vikash Kumar Chelsea Finn Aravind Rajeswaran
+	Do Deep Networks Transfer Invariances Across Classes?	2022	Allan Zhou Fahim Tajwar Alexander Robey Tom Knowles George J. Pappas Hamed Hassani Chelsea Finn
+	Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations	2022	Huaxiu Yao Xinyu Yang Allan Zhou Chelsea Finn
+	A Project on Cyclic Ordering of Some Families of Graphs	2022	Cedric Huchuan Xia Joe Zhang Allan Zhou
+	Unsupervised language models for disease variant prediction	2022	Allan Zhou Nicholas C. Landolfi Daniel O’Neill
+ PDF Chat	Noether Networks: Meta-Learning Useful Conserved Quantities	2021	Ferran Alet Dylan Doblar Allan Zhou Joshua B. Tenenbaum Kenji Kawaguchi Chelsea Finn
+	Discriminator Augmented Model-Based Reinforcement Learning	2021	Behzad Haghgoo Allan Zhou Archit Sharma Chelsea Finn
+	Noether Networks: Meta-Learning Useful Conserved Quantities	2021	Ferran Alet Dylan Doblar Allan Zhou Joshua B. Tenenbaum Kenji Kawaguchi Chelsea Finn
+	Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards	2020	Allan Zhou Eric Jang Daniel Kappler Alex Herzog Mohi Khansari Paul Wohlhart Yunfei Bai Mrinal Kalakrishnan Sergey Levine Chelsea Finn
+	Meta-Learning Symmetries by Reparameterization	2020	Allan Zhou Tom Knowles Chelsea Finn
+	Watch, Try, Learn: Meta-Learning from Demonstrations and Reward	2019	Allan Zhou Eric Jang Daniel Kappler Alex Herzog Mohi Khansari Paul Wohlhart Yunfei Bai Mrinal Kalakrishnan Sergey Levine Chelsea Finn
+ PDF Chat	Cost Functions for Robot Motion Style	2018	Allan Zhou Anca D. Dragan
+	Cost Functions for Robot Motion Style	2018	Allan Zhou Anca D. Dragan
+ PDF Chat	Expressive Robot Motion Timing	2017	Allan Zhou Dylan Hadfield-Menell Anusha Nagabandi Anca D. Dragan

Common Coauthors

Coauthor	Papers Together
Chelsea Finn	17
Yiding Jiang	3
Huaxiu Yao	3
Archit Sharma	3
Anca D. Dragan	3
Lirui Wang	3
Kenji Kawaguchi	2
J. Zico Kolter	2
Pete Florence	2
Sergey Levine	2
Rafael Rafailov	2
Daniel Kappler	2
Dylan Doblar	2
Ferran Alet	2
Christopher D. Manning	2
Alex Herzog	2
Samuel Sokota	2
Moo Jin Kim	2
Mohi Khansari	2
Joshua B. Tenenbaum	2
Eric Mitchell	2
Kaylee Burns	2
Kaien Yang	2
Mrinal Kalakrishnan	2
Eric Jang	2
Paul Wohlhart	2
Katherine Tian	2
Yunfei Bai	2
J. Zico Kolter	1
Fahim Tajwar	1
Yoonho Lee	1
Kaiqing Zhang	1
Joe Zhang	1
Pierluigi Zama Ramirez	1
Samuele Salti	1
Xinyu Yang	1
Dylan Hadfield-Menell	1
Sahaana Suri	1
Tong Mu	1
Hamed Hassani	1
Sadhika Malladi	1
Zhili Feng	1
Daniel O’Neill	1
Vikash Kumar	1
Adriano Cardace	1
Tom Knowles	1
Caroline Choi	1
Luigi Di Stefano	1
Tom Knowles	1
Winnie Xu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization	2016	Chelsea Finn Sergey Levine Pieter Abbeel	3
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	3
+	Learning to Learn	1998	Jonathan Baxter	3
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2018	Aravind Rajeswaran Vikash Kumar Abhishek Gupta Giulia Vezzani John Schulman Emanuel Todorov Sergey Levine	3
+	A Simple Neural Attentive Meta-Learner	2017	Nikhil Mishra Mostafa Rohaninejad Xi Chen Pieter Abbeel	2
+	Evolved Policy Gradients	2018	Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel	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
+	Deep reinforcement learning from human preferences	2017	Paul F. Christiano Jan Leike T. B. Brown Miljan Martic Shane Legg Dario Amodei	2
+ PDF Chat	Overcoming Exploration in Reinforcement Learning with Demonstrations	2018	Ashvin Nair Bob McGrew Marcin Andrychowicz Wojciech Zaremba Pieter Abbeel	2
+	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning	2018	Tianhe Yu Chelsea Finn Sudeep Dasari Annie Xie Tianhao Zhang Pieter Abbeel Sergey Levine	2
+	Deep reinforcement learning from human preferences	2017	Paul Christiano Jan Leike T. B. Brown Miljan Martic Shane Legg Dario Amodei	2
+	Learning to Learn: Meta-Critic Networks for Sample Efficient Learning	2017	Flood Sung Zhang Li Tao Xiang Timothy M. Hospedales Yongxin Yang	2
+	Some Considerations on Learning to Explore via Meta-Reinforcement Learning	2018	Bradly C. Stadie Ge Yang Rein Houthooft Xi Chen Yan Duan Yuhuai Wu Pieter Abbeel Ilya Sutskever	2
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	2
+	Task-Embedded Control Networks for Few-Shot Imitation Learning	2018	Stephen James Michael Bloesch Andrew J. Davison	2
+	Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning	2018	Anusha Nagabandi Ignasi Clavera Simin Liu Ronald S. Fearing Pieter Abbeel Sergey Levine Chelsea Finn	2
+	Meta-Reinforcement Learning of Structured Exploration Strategies	2018	Abhishek Gupta Russell Mendonca YuXuan Liu Pieter Abbeel Sergey Levine	2
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	2
+	One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL	2018	Tom Le Paine Sergio Gómez Colmenarejo Ziyu Wang Scott Reed Yusuf Aytar Tobias Pfaff Matthew W. Hoffman Gabriel Barth-Maron Serkan Cabi David Budden	2
+ PDF Chat	A Tutorial on Thompson Sampling	2018	Daniel Russo Benjamin Van Roy Abbas Kazerouni Ian Osband Zheng Wen	2
+	Maximum Entropy Deep Inverse Reinforcement Learning	2015	Markus Wulfmeier Peter Ondrúška Ingmar Posner	2
+	Meta Reinforcement Learning with Latent Variable Gaussian Processes	2018	Steindór Sæmundsson Katja Hofmann Marc Peter Deisenroth	2
+	Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor	2018	Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine	1
+	Generative Adversarial Imitation Learning	2016	Jonathan Ho Stefano Ermon	1
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	1
+	Grasp Pose Detection in Point Clouds	2017	Andreas ten Pas Marcus Gualtieri Kate Saenko Robert W. Platt	1
+	Meta-SGD: Learning to Learn Quickly for Few-Shot Learning	2017	Zhenguo Li Fengwei Zhou Fei Chen Hang Li	1
+	SMASH: One-Shot Model Architecture Search through HyperNetworks	2017	Andrew Brock Theodore Lim Jacob Ritchie Nick Weston	1
+	Exploring Model-based Planning with Policy Networks	2019	Tingwu Wang Jimmy Ba	1
+	Meta-Learning with Adaptive Layerwise Metric and Subspace.	2018	Yoonho Lee Seungjin Choi	1
+	Model-Based Reinforcement Learning for Atari	2019	Łukasz Kaiser Mohammad Babaeizadeh Piotr Miłoś Błażej Osiński Roy H. Campbell Konrad Czechowski Dumitru Erhan Chelsea Finn Piotr Kozakowski Sergey Levine	1
+	On Calibration of Modern Neural Networks	2017	Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger	1
+ PDF Chat	Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours	2016	Lerrel Pinto Abhinav Gupta	1
+ PDF Chat	Gaussian Processes for Data-Efficient Learning in Robotics and Control	2013	Marc Peter Deisenroth Dieter Fox Carl Edward Rasmussen	1
+	Selective Classification for Deep Neural Networks	2017	Yonatan Geifman Ran El‐Yaniv	1
+	How to train your MAML.	2018	Antreas Antoniou Harrison Edwards Amos Storkey	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Meta-Learning with Latent Embedding Optimization	2018	Andrei A. Rusu Dushyant Rao Jakub Sygnowski Oriol Vinyals Razvan Pascanu Simon Osindero Raia Hadsell	1
+	Prototypical Networks for Few-shot Learning	2017	Jake Snell Kevin Swersky Richard S. Zemel	1
+	Modular meta-learning	2018	Ferran Alet Tomás Lozano‐Pérez Leslie Pack Kaelbling	1
+	AutoAugment: Learning Augmentation Policies from Data	2018	Ekin D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le	1
+	Neural Architecture Search: A Survey	2018	Thomas Elsken Jan Hendrik Metzen Frank Hutter	1
+	Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics	2017	Jeffrey Mahler Jacky Liang Sherdil Niyaz Michael Laskey Richard Doan Xinyu Liu Juan Pablo Aparicio Ken Goldberg	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
+	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control	2018	Kendall Lowrey Aravind Rajeswaran Sham M. Kakade Emanuel Todorov Igor Mordatch	1
+	Gauge Equivariant Convolutional Networks and the Icosahedral CNN	2019	Taco Cohen Maurice Weiler Berkay Kicanaoglu Max Welling	1
+ PDF Chat	Deep learning for detecting robotic grasps	2015	Ian Lenz Honglak Lee Ashutosh Saxena	1
+	Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift	2019	Yaniv Ovadia Emily Fertig Jie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek	1
+	Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning	2018	Vladimir Feinberg Alvin Wan Ion Stoica Michael I. Jordan Joseph E. Gonzalez Sergey Levine	1
+	Equivariance Through Parameter-Sharing	2017	Siamak Ravanbakhsh Jeff Schneider Barnabás Póczos	1