Ce Zhang

1.8k total citations
35 papers, 690 citations indexed

About

Ce Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Ce Zhang has authored 35 papers receiving a total of 690 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Ce Zhang's work include Machine Learning and Data Classification (8 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Multimodal Machine Learning Applications (6 papers). Ce Zhang is often cited by papers focused on Machine Learning and Data Classification (8 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Multimodal Machine Learning Applications (6 papers). Ce Zhang collaborates with scholars based in China, United States and Switzerland. Ce Zhang's co-authors include Christopher Ré, Jaeho Shin, Sen Wu, Christopher De, Feiran Wang, Cheng Xu, Jianliang Xu, Jian Pei, Jude Shavlik and Feng Niu and has published in prestigious journals such as PLoS ONE, Environmental Science and Pollution Research and Neurocomputing.

In The Last Decade

Ce Zhang

34 papers receiving 669 citations

Peers

Ce Zhang
Comparison fields: 5 of 86
  • Artificial Intelligence 441
  • Information Systems 184
  • Computer Vision and Pattern Recognition 131
  • Computer Networks and Communications 123
  • Management Science and Operations Research 98
Replace Weiwen Liu with:
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Weiwen Liu China View profile →
Citations per field, relative to Ce Zhang
Ce Zhang · 1×
Citations per year, relative to Ce Zhang
Ce Zhang · 1×

Countries citing papers authored by Ce Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Ce Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ce Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Ce Zhang. A scholar is included among the top collaborators of Ce Zhang 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 Ce Zhang. Ce Zhang 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 6
2 2
3 9
4 0
5 4
6 12
7 6
8 7
9 1
10 2
11 86
12 7
13 38
14
Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
15
15 1
16
Decentralization Meets Quantization.
5
17 33
18
Building a Large-scale Multimodal Knowledge Base for Visual Question Answering.
12
19 57
20 20

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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