Stephan Zheng - RankMe

46 papers A* 10A 1Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. ICML Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham R. Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng
2025	J	`jnl`	EnCompass: Enhancing Agent Programming with Search Over Program Execution Paths. CoRR Zhening Li, Armando Solar-Lezama, Yisong Yue, Stephan Zheng
2024	A*	`conf`	Position: Social Environment Design Should be Further Developed for AI-based Policy-Making. ICML Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen
2024	J	`jnl`	Social Environment Design. CoRR Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen
2023	J	`jnl`	AI For Global Climate Cooperation 2023 Competition Proceedings. CoRR Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng
2023	A	`conf`	Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning. AAMAS Michael Curry, Alexander Trott, Soham Phade, Yu Bai, Stephan Zheng
2023	A*	`conf`	Learning to Play General-Sum Games against Multiple Boundedly Rational Agents. AAAI Eric Zhao, Alexander R. Trott, Caiming Xiong, Stephan Zheng
2023	J	`jnl`	MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. CoRR Arundhati Banerjee, Soham Phade, Stefano Ermon, Stephan Zheng
2023	J	`jnl`	MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. Trans. Mach. Learn. Res. Arundhati Banerjee, Soham R. Phade, Stefano Ermon, Stephan Zheng
2023	A*	`conf`	Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study. WWW Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes
2022	J	`jnl`	AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. CoRR Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng
2022	J	`jnl`	Finding General Equilibria in Many-Agent Economic Simulations Using Deep Reinforcement Learning. CoRR Michael Curry, Alexander Trott, Soham Phade, Yu Bai, Stephan Zheng
2022	J	`jnl`	Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning. Trans. Mach. Learn. Res. Tong Mu, Stephan Zheng, Alexander R. Trott
2022	J	`jnl`	Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal. CoRR Tong Mu, Stephan Zheng, Alexander Trott
2022	J	`jnl`	Using Reinforcement Learning to Study Platform Economies under Market Shocks. CoRR Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes
2022	J	`jnl`	WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU. J. Mach. Learn. Res. Tian Lan, Sunil Srinivasa, Huan Wang, Stephan Zheng
2021	J	`jnl`	Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist. CoRR Alexander Trott, Sunil Srinivasa, Douwe van der Wal, Sebastien Haneuse, Stephan Zheng
2021	J	`jnl`	ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations. CoRR Eric Zhao, Alexander R. Trott, Caiming Xiong, Stephan Zheng
2021	J	`jnl`	Robustness Gym: Unifying the NLP Evaluation Landscape. CoRR Karan Goel, Nazneen Fatema Rajani, Jesse Vig, Samson Tan, Jason Wu, Stephan Zheng, Caiming Xiong, Mohit Bansal, Christopher Ré
2021	J	`jnl`	Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer
2021	J	`jnl`	The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning. CoRR Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C. Parkes, Richard Socher
2021	J	`jnl`	WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU. CoRR Tian Lan, Sunil Srinivasa, Stephan Zheng
2020	A*	`conf`	ESPRIT: Explaining Solutions to Physical Reasoning Tasks. ACL Nazneen Fatema Rajani, Rui Zhang, Yi Chern Tan, Stephan Zheng, Jeremy Weiss, Aadit Vyas, Abhijit Gupta, Caiming Xiong, Richard Socher, Dragomir R. Radev
2020	J	`jnl`	ESPRIT: Explaining Solutions to Physical Reasoning Tasks. CoRR Nazneen Fatema Rajani, Rui Zhang, Yi Chern Tan, Stephan Zheng, Jeremy Weiss, Aadit Vyas, Abhijit Gupta, Caiming Xiong, Richard Socher, Dragomir R. Radev
2020	A*	`conf`	Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. ICML Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu
2020	J	`jnl`	Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. CoRR Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu
2020	J	`jnl`	The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies. CoRR Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, Richard Socher
2020	J	`jnl`	The Rise of AI-Driven Simulators: Building a New Crystal Ball. CoRR Ian T. Foster, David C. Parkes, Stephan Zheng
2019	—	`conf`	Generating Multi-Agent Trajectories using Programmatic Weak Supervision. ICLR (Poster) Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey
2019	A*	`conf`	Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards. NeurIPS Alexander Trott, Stephan Zheng, Caiming Xiong, Richard Socher
2019	J	`jnl`	Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards. CoRR Alexander Trott, Stephan Zheng, Caiming Xiong, Richard Socher
2019	J	`jnl`	Learning World Graphs to Accelerate Hierarchical Reinforcement Learning. CoRR Wenling Shang, Alexander Trott, Stephan Zheng, Caiming Xiong, Richard Socher
2019	A*	`conf`	NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. NeurIPS Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue
2019	J	`jnl`	NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. CoRR Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue
2019	A*	`conf`	On the Generalization Gap in Reparameterizable Reinforcement Learning. ICML Huan Wang, Stephan Zheng, Caiming Xiong, Richard Socher
2019	J	`jnl`	On the Generalization Gap in Reparameterizable Reinforcement Learning. CoRR Huan Wang, Stephan Zheng, Caiming Xiong, Richard Socher
2019	J	`jnl`	Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework. CoRR Michael Shum, Stephan Zheng, Wojciech Kryscinski, Caiming Xiong, Richard Socher
2018	J	`jnl`	Detecting Adversarial Examples via Neural Fingerprinting. CoRR Sumanth Dathathri, Stephan Zheng, Richard M. Murray, Yisong Yue
2018	J	`jnl`	Generative Multi-Agent Behavioral Cloning. CoRR Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey
2018	J	`jnl`	Multi-resolution Tensor Learning for Large-Scale Spatial Data. CoRR Stephan Zheng, Rose Yu, Yisong Yue
2017	J	`jnl`	Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories. CoRR Long Sha, Patrick Lucey, Stephan Zheng, Taehwan Kim, Yisong Yue, Sridha Sridharan
2017	J	`jnl`	Generating Long-term Trajectories Using Deep Hierarchical Networks. CoRR Stephan Zheng, Yisong Yue, Patrick Lucey
2017	J	`jnl`	Long-term Forecasting using Tensor-Train RNNs. CoRR Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue
2016	—	`conf`	Generating Long-term Trajectories Using Deep Hierarchical Networks. NIPS Stephan Zheng, Yisong Yue, Jennifer A. Hobbs
2016	A*	`conf`	Improving the Robustness of Deep Neural Networks via Stability Training. CVPR Stephan Zheng, Yang Song, Thomas Leung, Ian J. Goodfellow
2016	J	`jnl`	Improving the Robustness of Deep Neural Networks via Stability Training. CoRR Stephan Zheng, Yang Song, Thomas Leung, Ian J. Goodfellow