Stephan Zheng

Orcid: 0000-0002-7271-1616

According to our database¹, Stephan Zheng authored at least 37 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2024

Social Environment Design.

[BibT_eX]

[DOI]

CoRR, 2024

Position: Social Environment Design Should be Further Developed for AI-based Policy-Making.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

AI For Global Climate Cooperation 2023 Competition Proceedings.

[BibT_eX]

[DOI]

CoRR, 2023

Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2023, 2023

Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Learning to Play General-Sum Games against Multiple Boundedly Rational Agents.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning.

[BibT_eX]

[DOI]

Tong Mu

Stephan Zheng

Alexander R. Trott

Trans. Mach. Learn. Res., 2022

WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N.

[BibT_eX]

[DOI]

CoRR, 2022

Using Reinforcement Learning to Study Platform Economies under Market Shocks.

[BibT_eX]

[DOI]

CoRR, 2022

Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal.

[BibT_eX]

[DOI]

Tong Mu

Stephan Zheng

Alexander Trott

CoRR, 2022

Finding General Equilibria in Many-Agent Economic Simulations Using Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Simulation Intelligence: Towards a New Generation of Scientific Methods.

[BibT_eX]

[DOI]

CoRR, 2021

WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU.

[BibT_eX]

[DOI]

Tian Lan

Sunil Srinivasa

Stephan Zheng

CoRR, 2021

Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist.

[BibT_eX]

[DOI]

CoRR, 2021

The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations.

[BibT_eX]

[DOI]

CoRR, 2021

Robustness Gym: Unifying the NLP Evaluation Landscape.

[BibT_eX]

[DOI]

Karan Goel

Nazneen Fatema Rajani

CoRR, 2021

2020

The Rise of AI-Driven Simulators: Building a New Crystal Ball.

[BibT_eX]

[DOI]

Ian T. Foster

David C. Parkes

Stephan Zheng

CoRR, 2020

The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies.

[BibT_eX]

[DOI]

CoRR, 2020

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

ESPRIT: Explaining Solutions to Physical Reasoning Tasks.

[BibT_eX]

[DOI]

Nazneen Fatema Rajani

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework.

[BibT_eX]

[DOI]

CoRR, 2019

Learning World Graphs to Accelerate Hierarchical Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

NAOMI: Non-Autoregressive Multiresolution Sequence Imputation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Generalization Gap in Reparameterizable Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Generating Multi-Agent Trajectories using Programmatic Weak Supervision.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Generative Multi-Agent Behavioral Cloning.

[BibT_eX]

[DOI]

CoRR, 2018

Detecting Adversarial Examples via Neural Fingerprinting.

[BibT_eX]

[DOI]

CoRR, 2018

Multi-resolution Tensor Learning for Large-Scale Spatial Data.

[BibT_eX]

[DOI]

Stephan Zheng

Rose Yu

Yisong Yue

CoRR, 2018

2017

Long-term Forecasting using Tensor-Train RNNs.

[BibT_eX]

[DOI]

CoRR, 2017

Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories.

[BibT_eX]

[DOI]

CoRR, 2017

Generating Long-term Trajectories Using Deep Hierarchical Networks.

[BibT_eX]

[DOI]

Stephan Zheng

Yisong Yue

Patrick Lucey

CoRR, 2017

2016

Generating Long-term Trajectories Using Deep Hierarchical Networks.

[BibT_eX]

[DOI]

Stephan Zheng

Yisong Yue

Jennifer A. Hobbs

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improving the Robustness of Deep Neural Networks via Stability Training.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Stephan Zheng

Timeline

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