Patrick Gallinari
Impact in
- Artificial Intelligence top 0.5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Neural Networks and Applications
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
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- Complex Network Analysis Techniques
Papers in
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- Topic Modeling 49
- Natural Language Processing Techniques 45
- Text and Document Classification Technologies 44
- Neural Networks and Applications 29
- Advanced Graph Neural Networks 17
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- Data Management and Algorithms 23
- Co-authors
- Ludovic Denoyer (51 shared papers)Léon Bottou (5 shared papers)Massih-Reza Amini (18 shared papers)Antoine Bordes (3 shared papers)Nicolas Usunier (19 shared papers)Benjamin Piwowarski (20 shared papers)Sylvain Lamprier (13 shared papers)Yann Guermeur (3 shared papers)
In The Last Decade
Patrick Gallinari
220 papers receiving 3.8k citations
Patrick Gallinari's Hit Papers
Peers
Comparison fields: 5 of 170
- Artificial Intelligence 2.7k
- Statistical and Nonlinear Physics 553
- Computer Vision and Pattern Recognition 936
- Computational Mathematics 25
- Signal Processing 450
Countries citing papers authored by Patrick Gallinari
This map shows the geographic impact of Patrick Gallinari'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 Patrick Gallinari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Gallinari more than expected).
Fields of papers citing papers by Patrick Gallinari
This network shows the impact of papers produced by Patrick Gallinari. 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 Patrick Gallinari. The network helps show where Patrick Gallinari may publish in the future.
Co-authors
The 25 scholars most cited alongside Patrick Gallinari, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 244 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition Hit paper breakdown → | 2015 | 400 |
| 2 | SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent | 2009 | 217 |
| 3 | 1999 | 189 | |
| 4 | 2013 | 136 | |
| 5 | 2011 | 127 | |
| 6 | 2007 | 117 | |
| 7 | 2009 | 111 | |
| 8 | 1991 | 110 | |
| 9 | 2016 | 110 | |
| 10 | 1999 | 92 | |
| 11 | 2014 | 91 | |
| 12 | 2004 | 82 | |
| 13 | 2014 | 80 | |
| 14 | 2002 | 77 | |
| 15 | 1996 | 70 | |
| 16 | 2007 | 60 | |
| 17 | 2017 | 59 | |
| 18 | 2013 | 52 | |
| 19 | 2007 | 51 | |
| 20 | Normalizing Kalman Filters for Multivariate Time Series Analysis | 2020 | 45 |
About Patrick Gallinari
Patrick Gallinari is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 244 papers that have together received 4.1k indexed citations. Recurring topics across this work include Topic Modeling (49 papers), Natural Language Processing Techniques (45 papers), Text and Document Classification Technologies (44 papers), Neural Networks and Applications (29 papers), Web Data Mining and Analysis (25 papers), Data Management and Algorithms (23 papers), Image Retrieval and Classification Techniques (20 papers) and Advanced Graph Neural Networks (17 papers). The work is most often cited by research in Artificial Intelligence (2.7k citations), Statistical and Nonlinear Physics (553 citations), Computer Vision and Pattern Recognition (936 citations), Computational Mathematics (25 citations) and Signal Processing (450 citations). Patrick Gallinari has collaborated with scholars based in France, China and Italy. Frequent co-authors include Ludovic Denoyer, Léon Bottou, Massih-Reza Amini, Antoine Bordes, Nicolas Usunier, Benjamin Piwowarski, Sylvain Lamprier, Yann Guermeur, Sylvie Thiria and Philippe J. Leray. Their work appears in journals such as Lecture notes in computer science, ACM SIGIR Forum, Neurocomputing, Machine Learning and Data Mining and Knowledge Discovery.
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.