Amy Zhang - RankMe

143 papers A* 40A 4Misc 1Journal 92Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Factored Latent Action World Models. CoRR Zizhao Wang, Chang Shi, Jiaheng Hu, Kevin Rohling, Roberto Martín-Martín, Amy Zhang, Peter Stone
2026	J	`jnl`	Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion. CoRR Dan Haramati, Carl Qi, Tal Daniel, Amy Zhang, Aviv Tamar, George Konidaris
2026	J	`jnl`	Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models. CoRR Pranaya Jajoo, Harshit Sikchi, Siddhant Agarwal, Amy Zhang, Scott Niekum, Martha White
2025	A*	`conf`	An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. ICLR Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang
2025	J	`jnl`	An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. CoRR Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang
2025	J	`jnl`	Augmented Conditioning Is Enough For Effective Training Image Generation. CoRR Jiahui Chen, Amy Zhang, Adriana Romero-Soriano
2025	J	`jnl`	Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks. CoRR Viraj Joshi, Zifan Xu, Bo Liu, Peter Stone, Amy Zhang
2025	J	`jnl`	CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance. CoRR Arthur Zhang, Harshit Sikchi, Amy Zhang, Joydeep Biswas
2025	A*	`conf`	EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. ICLR Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang
2025	J	`jnl`	Fast Adaptation with Behavioral Foundation Models. CoRR Harshit Sikchi, Andrea Tirinzoni, Ahmed Touati, Yingchen Xu, Anssi Kanervisto, Scott Niekum, Amy Zhang, Alessandro Lazaric, Matteo Pirotta
2025	J	`jnl`	Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation. CoRR Sangmin Jung, Utkarsh Nath, Yezhou Yang, Giulia Pedrielli, Joydeep Biswas, Amy Zhang, Hassan Ghasemzadeh, Pavan K. Turaga
2025	J	`jnl`	Information-Theoretic Reward Decomposition for Generalizable RLHF. CoRR Liyuan Mao, Haoran Xu, Amy Zhang, Weinan Zhang, Chenjia Bai
2025	A*	`conf`	Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory. ICLR Alexander Levine, Peter Stone, Amy Zhang
2025	A*	`conf`	MaestroMotif: Skill Design from Artificial Intelligence Feedback. ICLR Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro
2025	A*	`conf`	Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. ICLR Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2025	J	`jnl`	Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. CoRR Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2025	J	`jnl`	Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets. CoRR Alexander Levine, Peter Stone, Amy Zhang
2025	A*	`conf`	Proto Successor Measure: Representing the Behavior Space of an RL Agent. ICML Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang
2025	J	`jnl`	Reevaluating Policy Gradient Methods for Imperfect-Information Games. CoRR Max Rudolph, Nathan Lichtle, Sobhan Mohammadpour, Alexandre M. Bayen, J. Zico Kolter, Amy Zhang, Gabriele Farina, Eugene Vinitsky, Samuel Sokota
2025	—	`conf`	StitchLLM: Serving LLMs, One Block at a Time. ACL (1) Bodun Hu, Shuozhe Li, Saurabh Agarwal, Myungjin Lee, Akshay Jajoo, Jiamin Li, Le Xu, Geon-Woo Kim, Donghyun Kim, Hong Xu, Amy Zhang, Aditya Akella
2025	A*	`conf`	Towards General-Purpose Model-Free Reinforcement Learning. ICLR Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat
2025	J	`jnl`	Towards General-Purpose Model-Free Reinforcement Learning. CoRR Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat
2024	Misc	`conf`	A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRL Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024	J	`jnl`	A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRR Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024	A	`conf`	A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem. AAMAS Paul Barde, Jakob N. Foerster, Derek Nowrouzezahrai, Amy Zhang
2024	A*	`conf`	AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers. NeurIPS Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu
2024	J	`jnl`	AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers. CoRR Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu
2024	—	`conf`	An investigation of time reversal symmetry in reinforcement learning. L4DC Brett Barkley, Amy Zhang, David Fridovich-Keil
2024	J	`jnl`	Automated Discovery of Functional Actual Causes in Complex Environments. CoRR Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum
2024	J	`jnl`	CAT: Caution Aware Transfer in Reinforcement Learning via Distributional Risk. CoRR Mohamad Fares El Hajj Chehade, Amrit Singh Bedi, Amy Zhang, Hao Zhu
2024	J	`jnl`	Diffusion World Model. CoRR Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng
2024	A*	`conf`	Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning. NeurIPS Liyuan Mao, Haoran Xu, Xianyuan Zhan, Weinan Zhang, Amy Zhang
2024	J	`jnl`	Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning. CoRR Liyuan Mao, Haoran Xu, Weinan Zhang, Xianyuan Zhan, Amy Zhang
2024	A*	`conf`	Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. ICLR Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum
2024	J	`jnl`	EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. CoRR Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang
2024	A*	`conf`	Efficient Reinforcement Learning by Discovering Neural Pathways. NeurIPS Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Amy Zhang, Alessandro Sordoni, Doina Precup
2024	A*	`conf`	Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks. ICLR Edwin Zhang, Yujie Lu, Shinda Huang, William Yang Wang, Amy Zhang
2024	J	`jnl`	Learning Action-based Representations Using Invariance. RLJ Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024	J	`jnl`	Learning Action-based Representations Using Invariance. CoRR Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024	J	`jnl`	Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory. CoRR Alexander Levine, Peter Stone, Amy Zhang
2024	J	`jnl`	MaestroMotif: Skill Design from Artificial Intelligence Feedback. CoRR Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro
2024	A*	`conf`	Motif: Intrinsic Motivation from Artificial Intelligence Feedback. ICLR Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
2024	J	`jnl`	Multistep Inverse Is Not All You Need. RLJ Alexander Levine, Peter Stone, Amy Zhang
2024	J	`jnl`	Multistep Inverse Is Not All You Need. CoRR Alexander Levine, Peter Stone, Amy Zhang
2024	J	`jnl`	Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback. CoRR Qinqing Zheng, Mikael Henaff, Amy Zhang, Aditya Grover, Brandon Amos
2024	J	`jnl`	Proto Successor Measure: Representing the Space of All Possible Solutions of Reinforcement Learning. CoRR Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang
2024	J	`jnl`	RL Zero: Zero-Shot Language to Behaviors without any Supervision. CoRR Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum
2024	J	`jnl`	Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. CoRR Caleb Chuck, Carl Qi, Michael J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum
2024	A*	`conf`	Score Models for Offline Goal-Conditioned Reinforcement Learning. ICLR Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
2024	A*	`conf`	SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. NeurIPS Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2024	J	`jnl`	SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. CoRR Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2024	J	`jnl`	Structure in Deep Reinforcement Learning: A Survey and Open Problems. J. Artif. Intell. Res. Aditya Mohan, Amy Zhang, Marius Lindauer
2024	A*	`conf`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2024	J	`jnl`	Unified Auto-Encoding with Masked Diffusion. CoRR Philippe Hansen-Estruch, Sriram Vishwanath, Amy Zhang, Manan Tomar
2024	A*	`conf`	When should we prefer Decision Transformers for Offline Reinforcement Learning? ICLR Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang
2024	A*	`conf`	Zero-Shot Reinforcement Learning via Function Encoders. ICML Tyler Ingebrand, Amy Zhang, Ufuk Topcu
2024	J	`jnl`	Zero-Shot Reinforcement Learning via Function Encoders. CoRR Tyler Ingebrand, Amy Zhang, Ufuk Topcu
2023	J	`jnl`	A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem. CoRR Paul Barde, Jakob N. Foerster, Derek Nowrouzezahrai, Amy Zhang
2023	J	`jnl`	A Survey of Zero-shot Generalisation in Deep Reinforcement Learning. J. Artif. Intell. Res. Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel
2023	A*	`conf`	Accelerating Exploration with Unlabeled Prior Data. NeurIPS Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	J	`jnl`	Accelerating Exploration with Unlabeled Prior Data. CoRR Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	J	`jnl`	An Investigation of Time Reversal Symmetry in Reinforcement Learning. CoRR Brett Barkley, Amy Zhang, David Fridovich-Keil
2023	A*	`conf`	AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. HPCA Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh
2023	A*	`conf`	BC-IRL: Learning Generalizable Reward Functions from Demonstrations. ICLR Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier
2023	J	`jnl`	BC-IRL: Learning Generalizable Reward Functions from Demonstrations. CoRR Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier
2023	J	`jnl`	Generalization Across Observation Shifts in Reinforcement Learning. CoRR Anuj Mahajan, Amy Zhang
2023	A*	`conf`	Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. ICLR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	J	`jnl`	Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods. CoRR Harshit Sikchi, Amy Zhang, Scott Niekum
2023	J	`jnl`	Improving Generalization with Approximate Factored Value Functions. Trans. Mach. Learn. Res. Shagun Sodhani, Sergey Levine, Amy Zhang
2023	A*	`conf`	LIV: Language-Image Representations and Rewards for Robotic Control. ICML Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman
2023	J	`jnl`	LIV: Language-Image Representations and Rewards for Robotic Control. CoRR Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman
2023	A*	`conf`	Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
2023	J	`jnl`	Learning Representations for Pixel-based Control: What Matters and Why? Trans. Mach. Learn. Res. Manan Tomar, Utkarsh A. Mishra, Amy Zhang, Matthew E. Taylor
2023	J	`jnl`	Motif: Intrinsic Motivation from Artificial Intelligence Feedback. CoRR Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
2023	J	`jnl`	Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. CoRR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	A*	`conf`	Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. ICML Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang
2023	J	`jnl`	Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. CoRR Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang
2023	A*	`conf`	Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability. NeurIPS Hanlin Zhu, Amy Zhang
2023	J	`jnl`	Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability. CoRR Hanlin Zhu, Amy Zhang
2023	A	`conf`	Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL. UAI Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu
2023	J	`jnl`	Score Models for Offline Goal-Conditioned Reinforcement Learning. CoRR Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
2023	J	`jnl`	Sequence Modeling is a Robust Contender for Offline Reinforcement Learning. CoRR Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang
2023	J	`jnl`	Structure in Reinforcement Learning: A Survey and Open Problems. CoRR Aditya Mohan, Amy Zhang, Marius Lindauer
2023	J	`jnl`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. CoRR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2023	A*	`conf`	VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. ICLR Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang
2023	J	`jnl`	f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences. CoRR Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang
2023	A*	`conf`	f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. NeurIPS Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang
2022	J	`jnl`	AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks. CoRR Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh
2022	A*	`conf`	Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. ICML Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine
2022	J	`jnl`	Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning. CoRR Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine
2022	—	`conf`	Block Contextual MDPs for Continual Learning. L4DC Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang
2022	J	`jnl`	Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning. CoRR Chris Lengerich, Gabriel Synnaeve, Amy Zhang, Hugh Leather, Kurt Shuster, François Charton, Charysse Redwood
2022	A*	`conf`	Denoised MDPs: Learning World Models Better Than the World Itself. ICML Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
2022	J	`jnl`	Denoised MDPs: Learning World Models Better Than the World Itself. CoRR Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
2022	J	`jnl`	LAD: Language Augmented Diffusion for Reinforcement Learning. CoRR Edwin Zhang, Yujie Lu, William Wang, Amy Zhang
2022	J	`jnl`	Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
2022	A*	`conf`	Online Decision Transformer. ICML Qinqing Zheng, Amy Zhang, Aditya Grover
2022	J	`jnl`	Online Decision Transformer. CoRR Qinqing Zheng, Amy Zhang, Aditya Grover
2022	A*	`conf`	Robust Policy Learning over Multiple Uncertainty Sets. ICML Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang
2022	J	`jnl`	Robust Policy Learning over Multiple Uncertainty Sets. CoRR Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang
2022	J	`jnl`	VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. CoRR Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang
2021	J	`jnl`	A Survey of Generalisation in Deep Reinforcement Learning. CoRR Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel
2021	J	`jnl`	Block Contextual MDPs for Continual Learning. CoRR Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang
2021	A*	`conf`	Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus
2021	A*	`conf`	Learning Invariant Representations for Reinforcement Learning without Reconstruction. ICLR Amy Zhang, Rowan Thomas McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
2021	J	`jnl`	Learning Representations for Pixel-based Control: What Matters and Why? CoRR Manan Tomar, Utkarsh A. Mishra, Amy Zhang, Matthew E. Taylor
2021	A*	`conf`	Learning Robust State Abstractions for Hidden-Parameter Block MDPs. ICLR Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
2021	J	`jnl`	MBRL-Lib: A Modular Library for Model-based Reinforcement Learning. CoRR Luis Pineda, Brandon Amos, Amy Zhang, Nathan O. Lambert, Roberto Calandra
2021	J	`jnl`	Model-Invariant State Abstractions for Model-Based Reinforcement Learning. CoRR Manan Tomar, Amy Zhang, Roberto Calandra, Matthew E. Taylor, Joelle Pineau
2021	A*	`conf`	Multi-Task Reinforcement Learning with Context-based Representations. ICML Shagun Sodhani, Amy Zhang, Joelle Pineau
2021	J	`jnl`	Multi-Task Reinforcement Learning with Context-based Representations. CoRR Shagun Sodhani, Amy Zhang, Joelle Pineau
2021	A*	`conf`	Out-of-Distribution Generalization via Risk Extrapolation (REx). ICML David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville
2021	J	`jnl`	Provably Efficient Representation Learning in Low-rank Markov Decision Processes. CoRR Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu
2021	A*	`conf`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. NeurIPS Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2021	J	`jnl`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. CoRR Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2020	J	`jnl`	Intervention Design for Effective Sim2Real Transfer. CoRR Melissa Mozifian, Amy Zhang, Joelle Pineau, David Meger
2020	A*	`conf`	Invariant Causal Prediction for Block MDPs. ICML Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
2020	J	`jnl`	Invariant Causal Prediction for Block MDPs. CoRR Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
2020	J	`jnl`	Learning Invariant Representations for Reinforcement Learning without Reconstruction. CoRR Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
2020	J	`jnl`	Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP. CoRR Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
2020	J	`jnl`	Out-of-Distribution Generalization via Risk Extrapolation (REx). CoRR David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Rémi Le Priol, Aaron C. Courville
2020	—	`conf`	Plan2Vec: Unsupervised Representation Learning by Latent Plans. L4DC Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra
2020	J	`jnl`	Plan2Vec: Unsupervised Representation Learning by Latent Plans. CoRR Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra
2020	A	`conf`	Stable Policy Optimization via Off-Policy Divergence Regularization. UAI Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent
2020	J	`jnl`	Stable Policy Optimization via Off-Policy Divergence Regularization. CoRR Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent
2019	J	`jnl`	Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus
2019	J	`jnl`	Learning Causal State Representations of Partially Observable Environments. CoRR Amy Zhang, Zachary C. Lipton, Luis Pineda, Kamyar Azizzadenesheli, Anima Anandkumar, Laurent Itti, Joelle Pineau, Tommaso Furlanello
2018	J	`jnl`	A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning. CoRR Amy Zhang, Nicolas Ballas, Joelle Pineau
2018	A*	`conf`	Composable Planning with Attributes. ICML Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus
2018	J	`jnl`	Composable Planning with Attributes. CoRR Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar, Rob Fergus, Arthur Szlam
2018	—	`conf`	Decoupling Dynamics and Reward for Transfer Learning. ICLR (Workshop) Amy Zhang, Harsh Satija, Joelle Pineau
2018	J	`jnl`	Decoupling Dynamics and Reward for Transfer Learning. CoRR Amy Zhang, Harsh Satija, Joelle Pineau
2018	J	`jnl`	Natural Environment Benchmarks for Reinforcement Learning. CoRR Amy Zhang, Yuxin Wu, Joelle Pineau
2017	J	`jnl`	Building Detection from Satellite Images on a Global Scale. CoRR Amy Zhang, Xianming Liu, Andreas Gros, Tobias Tiecke
2017	J	`jnl`	Mapping the world population one building at a time. CoRR Tobias G. Tiecke, Xianming Liu, Amy Zhang, Andreas Gros, Nan Li, Gregory Yetman, Talip Kilic, Siobhan Murray, Brian Blankespoor, Espen B. Prydz, Hai-Anh H. Dang
2016	J	`jnl`	Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation. CoRR Xianming Liu, Amy Zhang, Tobias Tiecke, Andreas Gros, Thomas S. Huang
2015	J	`jnl`	Managing Your Private and Public Data: Bringing Down Inference Attacks Against Your Privacy. IEEE J. Sel. Top. Signal Process. Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2015	J	`jnl`	PriView: Personalized Media Consumption Meets Privacy against Inference Attacks. IEEE Softw. Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Amy Zhang
2014	J	`jnl`	Guess Who Rated This Movie: Identifying Users Through Subspace Clustering. CoRR Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari
2014	J	`jnl`	Managing your Private and Public Data: Bringing down Inference Attacks against your Privacy. CoRR Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2013	—	`conf`	How to hide the elephant- or the donkey- in the room: Practical privacy against statistical inference for large data. GlobalSIP Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2012	J	`jnl`	Guess Who Rated This Movie: Identifying Users Through Subspace Clustering CoRR Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari
2012	A	`conf`	Guess Who Rated This Movie: Identifying Users Through Subspace Clustering. UAI Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari