Shiyu Liang

2.0k citations
20 papers · 221 indexed · h-index 9
Topics
Neural Networks and Applications (4 papers)Stochastic Gradient Optimization Techniques (4 papers)Advanced Neural Network Applications (3 papers)
Journals
SHILAP Revista de lepidopterologíaBloodPLoS ONE

In The Last Decade

Shiyu Liang

18 papers receiving 208 citations

Peers

Shiyu Liang
Comparison fields: 5 of 102
  • Artificial Intelligence 90
  • Molecular Biology 55
  • Computer Vision and Pattern Recognition 32
  • Immunology 13
  • Electrical and Electronic Engineering 11
Replace Md. Tabil Ahammed with:
Md. Tabil Ahammed Bangladesh
K Saravanan India
Vivek Bagaria United States
Chengcheng Ma China
Zheng Yuan China
Xuefeng Jiang China
Florian Haag Germany
Aijing Sun China
Shiyu Liang relative to Md. Tabil Ahammed Bangladesh Md. Tabil Ahammed's profile →
Citations per field
00.5×1.5×2.4×
Md. Tabil Ahammed · 1×
Citations per year

Countries citing papers authored by Shiyu Liang

Since Specialization
Citations

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

Fields of papers citing papers by Shiyu Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiyu Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Shiyu Liang. A scholar is included among the top collaborators of Shiyu Liang 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 Shiyu Liang. Shiyu Liang 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
#WorkIndexed citations
1 12
2 7
3 3
4 14
5 7
6 4
7 1
8 0
9 17
10 12
11 3
12 3
13 35
14 3
15
Understanding the Loss Surface of Neural Networks for Binary Classification
1
16 6
17 15
18
Principled Detection of Out-of-Distribution Examples in Neural Networks.
35
19
Why Deep Neural Networks
8
20 35

About Shiyu Liang

Shiyu Liang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Developmental Neuroscience, having authored 20 papers that have together received 221 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Stochastic Gradient Optimization Techniques (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (90 citations) and Computer Vision and Pattern Recognition (32 citations). Shiyu Liang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jiawei Luo, R. Srikant, Yixuan Li, Ruoyu Sun, Ramakrishnan Srikant, Tian Ding, Jason D. Lee, Shuai Lü, Xiaolin Yu and Rui‐tian Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.

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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