Jiechuan Jiang

489 citations
5 papers · 54 indexed · h-index 3
Co-authors
Zongqing Lu
Topics
Reinforcement Learning in Robotics (3 papers)Experimental Behavioral Economics Studies (1 paper)Complex Network Analysis Techniques (1 paper)
Journals
arXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence
Partner nations
China

In The Last Decade

Jiechuan Jiang

4 papers receiving 52 citations

Peers

Jiechuan Jiang
Comparison fields: 5 of 24
  • Artificial Intelligence 47
  • Computer Networks and Communications 13
  • Electrical and Electronic Engineering 8
  • Computer Vision and Pattern Recognition 6
  • Computational Theory and Mathematics 6
Replace Danilo Francati with:
Danilo Francati Italy
Avishay Yanai Israel
Sebastiaan de Hoogh Netherlands
Boyang Li China
Kallista Bonawitz United States
Björn Tackmann Switzerland
Isamu Teranishi Japan
Hossein Yalame Germany
Michel Tokic Germany
Edward Lockhart United Kingdom
Jiechuan Jiang relative to Danilo Francati Italy Danilo Francati's profile →
Citations per field
00.5×5.5×
Danilo Francati · 1×
Citations per year

Countries citing papers authored by Jiechuan Jiang

Since Specialization
Citations

This map shows the geographic impact of Jiechuan Jiang'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 Jiechuan Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiechuan Jiang more than expected).

Fields of papers citing papers by Jiechuan Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiechuan Jiang. 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 Jiechuan Jiang. The network helps show where Jiechuan Jiang may publish in the future.

Co-authorship network of co-authors of Jiechuan Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiechuan Jiang. A scholar is included among the top collaborators of Jiechuan Jiang 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 Jiechuan Jiang. Jiechuan Jiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1 0
2 2
3 2
4 4
5
Learning Attentional Communication for Multi-Agent Cooperation
46

About Jiechuan Jiang

Jiechuan Jiang is a scholar working on Safety Research, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 5 papers that have together received 54 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Experimental Behavioral Economics Studies (1 paper) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (47 citations), Computer Networks and Communications (13 citations) and Computer Science Applications (3 citations). Jiechuan Jiang has collaborated with scholars based in China. Frequent co-authors include Zongqing Lu. Their work appears in journals such as arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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