Leonardo Neves

1.2k total citations · 1 hit paper
26 papers, 642 citations indexed

About

Leonardo Neves is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Leonardo Neves has authored 26 papers receiving a total of 642 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 7 papers in Information Systems and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Leonardo Neves's work include Topic Modeling (13 papers), Natural Language Processing Techniques (7 papers) and Recommender Systems and Techniques (4 papers). Leonardo Neves is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (7 papers) and Recommender Systems and Techniques (4 papers). Leonardo Neves collaborates with scholars based in United States, Brazil and China. Leonardo Neves's co-authors include Vı́tor Carvalho, Neil Shah, Yozen Liu, Heng Ji, Di Lu, Meng Jiang, Oliver J. Woodford, Ning Zhang, Tong Zhao and Yun Wang and has published in prestigious journals such as Computers in Human Behavior, Future Generation Computer Systems and Clinics.

In The Last Decade

Leonardo Neves

25 papers receiving 623 citations

Hit Papers

Data Augmentation for Graph Neural Networks 2021 2026 2022 2024 2021 50 100 150 200

Peers

Leonardo Neves
Comparison fields: 5 of 82
  • Artificial Intelligence 511
  • Computer Vision and Pattern Recognition 171
  • Information Systems 86
  • Signal Processing 53
  • Statistical and Nonlinear Physics 50
Replace Steffen Eger with:
Steffen Eger Germany
Jialong Han China
Maíra Gatti de Bayser Brazil
Yifei Zhang China
Weiran Xu China
Nikolaos Pappas Switzerland
Wen Wu China
Steffen Eger Germany View profile →
Citations per field, relative to Leonardo Neves
Leonardo Neves · 1×
Citations per year, relative to Leonardo Neves
Leonardo Neves · 1×

Countries citing papers authored by Leonardo Neves

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Neves

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonardo Neves

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Neves. A scholar is included among the top collaborators of Leonardo Neves 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 Leonardo Neves. Leonardo Neves 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 0
2 3
3 2
4 2
5 4
6 27
7 23
8
Data Augmentation for Graph Neural Networks breakdown →
212
9 7
10 4
11 7
12 1
13
A Caption Is Worth A Thousand Images: Investigating Image Captions for Multimodal Named Entity Recognition.
3
14 8
15 24
16 7
17 49
18 173
19 3
20
Integrating Domain-Data Steering with Code-Profiling Tools to Debug Data-Intensive Workflows.
3

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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