Chuan Guo
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Control and Systems Engineering top 5%
- Signal Processing top 10%
- Computational Mechanics top 10%
- Topics
- Adversarial Robustness in Machine Learning (8 papers)Human Motion and Animation (7 papers)Human Pose and Action Recognition (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceControl and Systems Engineering
- Partner nations
- United StatesCanadaChina
In The Last Decade
Chuan Guo
26 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 571
- Computer Vision and Pattern Recognition 543
- Control and Systems Engineering 331
- Signal Processing 96
- Computational Mechanics 75
Countries citing papers authored by Chuan Guo
This map shows the geographic impact of Chuan Guo'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 Chuan Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chuan Guo more than expected).
Fields of papers citing papers by Chuan Guo
This network shows the impact of papers produced by Chuan Guo. 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 Chuan Guo. The network helps show where Chuan Guo may publish in the future.
Co-authorship network of co-authors of Chuan Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Chuan Guo. A scholar is included among the top collaborators of Chuan Guo 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 Chuan Guo. Chuan Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 29 | |
| 6 | 10 | |
| 7 | Generating Diverse and Natural 3D Human Motions from Textbreakdown → | 213 |
| 8 | 21 | |
| 9 | 55 | |
| 10 | 1 | |
| 11 | Making Paper Reviewing Robust to Bid Manipulation Attacks | 4 |
| 12 | Action2Motion | 4 |
| 13 | Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces | 15 |
| 14 | 52 | |
| 15 | TrojanNet: Exposing the Danger of Trojan Horse Attack on Neural Networks | 1 |
| 16 | Low Frequency Adversarial Perturbation | 3 |
| 17 | 2 | |
| 18 | On calibration of modern neural networksbreakdown → | 338 |
| 19 | Discovering and Exploiting Additive Structure for Bayesian Optimization | 29 |
| 20 | 1 |
About Chuan Guo
Chuan Guo is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 29 papers that have together received 1.1k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (8 papers), Human Motion and Animation (7 papers) and Human Pose and Action Recognition (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (543 citations), Artificial Intelligence (571 citations) and Control and Systems Engineering (331 citations). Chuan Guo has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Kilian Q. Weinberger, Geoff Pleiss, Yu Sun, Li Cheng, Shihao Zou, Sen Wang, Xinxin Zuo, Wei Ji, Xingyu Li and Minglun Gong. Their work appears in journals such as IEEE Access, ACM Transactions on Graphics and International Journal of Computer Vision.
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.