Guillaume Klein

616 total citations
10 papers, 104 citations indexed

About

Guillaume Klein is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Organic Chemistry. According to data from OpenAlex, Guillaume Klein has authored 10 papers receiving a total of 104 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Organic Chemistry. Recurrent topics in Guillaume Klein's work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Surfactants and Colloidal Systems (2 papers). Guillaume Klein is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Surfactants and Colloidal Systems (2 papers). Guillaume Klein collaborates with scholars based in France, Australia and Germany. Guillaume Klein's co-authors include Jean Sénellart, Vincent Nguyen, Y. Holl, Alexander M. Rush, Yuntian Deng, Yoon Kim, Anders Larsson, Pascal Marie, Mounir Maaloum and Marie Ernstsson and has published in prestigious journals such as Colloids and Surfaces A Physicochemical and Engineering Aspects, Tribology International and SIAM Journal on Control and Optimization.

In The Last Decade

Guillaume Klein

10 papers receiving 94 citations

Peers

Guillaume Klein
Comparison fields: 5 of 46
  • Artificial Intelligence 56
  • Computer Vision and Pattern Recognition 25
  • Organic Chemistry 17
  • Materials Chemistry 15
  • Mechanics of Materials 11
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Haoran Liao China
N. Kazeev Russia
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Tung Chou Taiwan
Sungil Kang South Korea
Gaurav Agrawal United States
Hongyu Hu United States
Kengo Watanabe Japan
Juncen Li China
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Citations per field, relative to Guillaume Klein
Guillaume Klein · 1×
Citations per year, relative to Guillaume Klein
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Countries citing papers authored by Guillaume Klein

Since Specialization
Citations

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

Fields of papers citing papers by Guillaume Klein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guillaume Klein

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

All Works

10 of 10 papers shown
# Work Indexed citations
1
The OpenNMT Neural Machine Translation Toolkit: 2020 Edition
16
2 4
3
OpenNMT: Neural Machine Translation Toolkit
27
4 10
5 4
6 2
7 10
8 3
9 26
10 2

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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