Ines Chami
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Neural Networks and Applications
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
Papers in
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- Multimodal Machine Learning Applications 3
- Image Retrieval and Classification Techniques 1
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- Advanced Graph Neural Networks 2
- Topic Modeling 1
- Co-authors
- Christopher Ré (3 shared papers)Frédéric Sala (1 shared paper)Da-Cheng Juan (1 shared paper)Sujith Ravi (1 shared paper)Avanika Narayan (1 shared paper)Laurel Orr (1 shared paper)Ranjay Krishna (1 shared paper)Li Fei-Fei (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (1 paper)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)PubMed (1 paper)Annual Meeting of the Association for Computational Linguistics (ACL) (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Ines Chami
6 papers receiving 496 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 309
- Computer Vision and Pattern Recognition 97
- Management Science and Operations Research 44
- Information Systems 39
- Computer Networks and Communications 32
Countries citing papers authored by Ines Chami
This map shows the geographic impact of Ines Chami'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 Ines Chami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ines Chami more than expected).
Fields of papers citing papers by Ines Chami
This network shows the impact of papers produced by Ines Chami. 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 Ines Chami. The network helps show where Ines Chami may publish in the future.
Co-authors
The 14 scholars most cited alongside Ines Chami, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 268 | |
| 2 | 2022 | 108 | |
| 3 | 2018 | 75 | |
| 4 | Hyperbolic Graph Convolutional Neural Networks. | 2019 | 46 |
| 5 | 2017 | 6 | |
| 6 | Image Annotation and Two Paths to Text Illustration. | 2016 | 2 |
About Ines Chami
Ines Chami is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Management Science and Operations Research, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 6 papers that have together received 505 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (3 papers), Advanced Graph Neural Networks (2 papers), Topic Modeling (1 paper), Image Retrieval and Classification Techniques (1 paper) and Data Quality and Management (1 paper). The work is most often cited by research in Artificial Intelligence (309 citations), Computer Vision and Pattern Recognition (97 citations), Management Science and Operations Research (44 citations), Information Systems (39 citations) and Computer Networks and Communications (32 citations). Ines Chami has collaborated with scholars based in United States and France. Frequent co-authors include Christopher Ré, Frédéric Sala, Da-Cheng Juan, Sujith Ravi, Avanika Narayan, Laurel Orr, Ranjay Krishna, Li Fei-Fei, Michael S. Bernstein and Jure Leskovec. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings, HAL (Le Centre pour la Communication Scientifique Directe), PubMed and Annual Meeting of the Association for Computational Linguistics (ACL).
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.