Yinglong Xia

956 citations
53 papers · 437 · h-index 13

Impact in

Papers in

Yinglong Xia

49 papers receiving 422 citations

Peers

Yinglong Xia
Comparison fields: 5 of 57
  • Artificial Intelligence 326
  • Statistical and Nonlinear Physics 85
  • Computer Vision and Pattern Recognition 96
  • Information Systems 87
  • Computer Networks and Communications 75
Replace Zekai J. Gao with:
Zekai J. Gao United States
Bart Bogaerts Belgium
Baoxu Shi United States
Shaohua Fan China
Zaixi Zhang China
Javad Azimi United States
Hongfei Yan China
Jo Devriendt Belgium
Alessandro Epasto United States
Yuntao Jia United States
Yinglong Xia relative to Zekai J. Gao United States Zekai J. Gao's profile →
Citations per field
00.5×8.4×
Zekai J. Gao · 1×
Citations per year

Countries citing papers authored by Yinglong Xia

Since Specialization
Citations

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

Fields of papers citing papers by Yinglong Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yinglong Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yinglong Xia Line = papers co-authored together Yinglong Xia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202437
2 202128
3 202228
4 202227
5 202226
6 200821
7 202020
8 202319
9 202019
10 201917
11 200716
12 200916
13 201015
14 201812
15 201912
16 201611
17 20209
18 20228
19 20087
20 20197

About Yinglong Xia

Yinglong Xia is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems, having authored 53 papers that have together received 437 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (18 papers), Bayesian Modeling and Causal Inference (18 papers), Complex Network Analysis Techniques (16 papers), Graph Theory and Algorithms (7 papers), Data Management and Algorithms (6 papers), Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (5 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (326 citations), Statistical and Nonlinear Physics (85 citations), Computer Vision and Pattern Recognition (96 citations), Information Systems (87 citations) and Computer Networks and Communications (75 citations). Yinglong Xia has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Viktor K. Prasanna, Hanghang Tong, Jiebo Luo, Si Zhang, Jiejun Xu, Jian Kang, Long Jin, Lihui Liu, Nan Cao and Yunsong Guo. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of Parallel and Distributed Computing, IEEE Transactions on Parallel and Distributed Systems, Knowledge and Information Systems and IEEE Transactions on Computers.

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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