Liang Yang

1.3k total citations
73 papers, 832 citations indexed

About

Liang Yang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Liang Yang has authored 73 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 14 papers in Statistical and Nonlinear Physics. Recurrent topics in Liang Yang's work include Advanced Graph Neural Networks (29 papers), Complex Network Analysis Techniques (14 papers) and Brain Tumor Detection and Classification (8 papers). Liang Yang is often cited by papers focused on Advanced Graph Neural Networks (29 papers), Complex Network Analysis Techniques (14 papers) and Brain Tumor Detection and Classification (8 papers). Liang Yang collaborates with scholars based in China, United States and United Arab Emirates. Liang Yang's co-authors include J. H. Lilly, Di Jin, Yuanfang Guo, Xiaochun Cao, Junhua Gu, Chuan Wang, Bo Yang, Dongxiao He, Chun‐Bo Teng and Mei He and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Liang Yang

63 papers receiving 813 citations

Peers

Liang Yang
Comparison fields: 5 of 105
  • Artificial Intelligence 461
  • Computer Vision and Pattern Recognition 190
  • Statistical and Nonlinear Physics 176
  • Biomedical Engineering 128
  • Information Systems 121
Replace Zhe Xue with:
Zhe Xue China
Junxiang Wang China
You Zhou China
Yicheng Pan Taiwan
Qiang Cai China
Ni Li China
Satish Chandra India
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Citations per field, relative to Liang Yang
Liang Yang · 1×
Citations per year, relative to Liang Yang
Liang Yang · 1×

Countries citing papers authored by Liang Yang

Since Specialization
Citations

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

Fields of papers citing papers by Liang Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Yang

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 2
3 1
4 0
5 2
6 2
7 0
8 5
9 4
10 4
11 2
12 2
13 12
14
Diverse Message Passing for Attribute with Heterophily
20
15 8
16 18
17
Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes
2
18
A Refined Margin Distribution Analysis for Forest Representation Learning
5
19 29
20 11

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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