Jianmin Guo

487 citations
9 papers · 116 indexed · h-index 6
Topics
Adversarial Robustness in Machine Learning (4 papers)Computational Drug Discovery Methods (3 papers)Anomaly Detection Techniques and Applications (3 papers)
Partner nations
ChinaUnited StatesCanada

In The Last Decade

Jianmin Guo

9 papers receiving 115 citations

Peers

Jianmin Guo
Comparison fields: 5 of 47
  • Artificial Intelligence 74
  • Signal Processing 28
  • Electrical and Electronic Engineering 26
  • Computer Vision and Pattern Recognition 18
  • Computer Networks and Communications 17
Replace Julien Iguchi-Cartigny with:
Julien Iguchi-Cartigny France
Riadh Robbana Tunisia
Peter C. Dillinger United States
Kai Xiao United States
Baptiste Rozière United States
Ziqi Yang China
Maksym Andriushchenko Germany
Nicolas Palix Denmark
Jacob Buckman United States
Jonathan Uesato United States
Jianmin Guo relative to Julien Iguchi-Cartigny France Julien Iguchi-Cartigny's profile →
Citations per field
00.5×10×16.5×
Julien Iguchi-Cartigny · 1×
Citations per year

Countries citing papers authored by Jianmin Guo

Since Specialization
Citations

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

Fields of papers citing papers by Jianmin Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianmin Guo

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 1
2 1
3 3
4 8
5 24
6 42
7 13
8 18
9
RNN-Test: Adversarial Testing Framework for Recurrent Neural Network Systems.
6

About Jianmin Guo

Jianmin Guo is a scholar working on Toxicology, Software and Computational Theory and Mathematics, having authored 9 papers that have together received 116 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Computational Drug Discovery Methods (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Software (10 citations), Signal Processing (28 citations) and Artificial Intelligence (74 citations). Jianmin Guo has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yu Jiang, Yongqiang Tian, Quan Zhang, Xun Jiao, Yue Zhao, Houbing Song, Yiwei Wang, Jianming Wu, Binyou Wang and Jia Lai. Their work appears in journals such as BMC Bioinformatics, Pharmaceutics and IEEE Transactions on Reliability.

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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