Stephan Zheng

1.7k total citations · 1 hit paper
14 papers, 560 citations indexed

About

Stephan Zheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Economics and Econometrics. According to data from OpenAlex, Stephan Zheng has authored 14 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Economics and Econometrics. Recurrent topics in Stephan Zheng's work include Reinforcement Learning in Robotics (3 papers), Particle Detector Development and Performance (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Stephan Zheng is often cited by papers focused on Reinforcement Learning in Robotics (3 papers), Particle Detector Development and Performance (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Stephan Zheng collaborates with scholars based in United States, United Kingdom and Switzerland. Stephan Zheng's co-authors include Yang Song, Thomas Leung, Ian Goodfellow, Yisong Yue, Anima Anandkumar, Richard Socher, Rose Yu, David C. Parkes, Sunil Srinivasa and Adam Gibson and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Science Advances.

In The Last Decade

Stephan Zheng

14 papers receiving 547 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Improving the Robustness of Deep Neural Networks via Stability Training

2016 312 citations Stephan Zheng, Yang Song et al. profile →

Peers

Countries citing papers authored by Stephan Zheng

Since Specialization

Citations

This map shows the geographic impact of Stephan Zheng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stephan Zheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Zheng more than expected).

Fields of papers citing papers by Stephan Zheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephan Zheng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stephan Zheng. The network helps show where Stephan Zheng may publish in the future.

Co-authorship network of co-authors of Stephan Zheng

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Zheng. A scholar is included among the top collaborators of Stephan Zheng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stephan Zheng. Stephan Zheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

#	Work	Indexed citations
1	Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study 2023 ·(unknown), (unknown), (unknown), (unknown), (unknown), Stephan Zheng, David C. Parkes	6
2	The AI Economist: Taxation policy design via two-level deep multiagent reinforcement learning 2022 ·Science Advances ·Stephan Zheng, (unknown), Sunil Srinivasa, David C. Parkes, Richard Socher	51
3	Technology readiness levels for machine learning systems 2022 ·Nature Communications ·Alexander Lavin, (unknown), (unknown), (unknown), Dava Newman, S. Ganguly, Danny B. Lange, Atılım Güneş Baydin, Amit Sharma, Adam Gibson, Stephan Zheng, Eric P. Xing, Chris A. Mattmann, James F. Parr, Yarin Gal	78
4	AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N 2022 ·SSRN Electronic Journal ·(unknown), (unknown), (unknown), Sunil Srinivasa, Yang Zhang, (unknown), Yoshua Bengio, Stephan Zheng	1
5	On the Generalization Gap in Reparameterizable Reinforcement Learning 2019 ·arXiv (Cornell University) ·Huan Wang, Stephan Zheng, Caiming Xiong, Richard Socher	3
6	Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards 2019 ·arXiv (Cornell University) ·(unknown), Stephan Zheng, Caiming Xiong, Richard Socher	13
7	Generating Multi-Agent Trajectories using Programmatic Weak Supervision 2018 ·CaltechAUTHORS (California Institute of Technology) ·(unknown), Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey	4
8	The HEP.TrkX Project: Deep Learning for Particle Tracking 2018 ·Journal of Physics Conference Series ·Aristeidis Tsaris, Dustin Anderson, J. Bendavid, P. Calafiura, G. B. Cerati, (unknown), Steven Farrell, L. Gray, (unknown), Jim Kowalkowski, Mayur Mudigonda, Prabhat, (unknown), (unknown), Jean-Roch Vlimant, Stephan Zheng, Daniel V. Zurawski	12
9	Structured Exploration via Hierarchical Variational Policy Networks 2018 ·Stephan Zheng, Yisong Yue	1
10	Long Range Sequence Generation via Multiresolution Adversarial Training 2018 ·Yukai Liu, Rose Yu, Stephan Zheng, Yisong Yue	1
11	The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking 2017 ·SHILAP Revista de lepidopterología ·Steven Farrell, Dustin Anderson, P. Calafiura, G. B. Cerati, L. Gray, Jim Kowalkowski, Mayur Mudigonda, Prabhat, Panagiotis Spentzouris, (unknown), Aristeidis Tsaris, Jean-Roch Vlimant, Stephan Zheng	22
12	Measuring the Robustness of Neural Networks via Minimal Adversarial Examples 2017 ·CaltechAUTHORS (California Institute of Technology) ·Sumanth Dathathri, Stephan Zheng, Sicun Gao, Richard M. Murray	1
13	Long-term Forecasting using Tensor-Train RNNs 2017 ·CaltechAUTHORS (California Institute of Technology) ·Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue	55
14	Improving the Robustness of Deep Neural Networks via Stability Training breakdown → 2016 ·Stephan Zheng, Yang Song, Thomas Leung, Ian Goodfellow	312

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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