Patrick Gallinari
- Artificial Intelligence top 2%
- Neural Networks and Applications 21
- Topic Modeling 17
- Natural Language Processing Techniques 15
- Text and Document Classification Technologies 12
- Speech Recognition and Synthesis 10
- Advanced Graph Neural Networks 9
- Signal Processing top 5%
- Speech and Audio Processing 6
- Information Systems top 5%
- Recommender Systems and Techniques 6
Patrick Gallinari
79 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 151
- Artificial Intelligence 726
- Signal Processing 201
- Computer Vision and Pattern Recognition 242
- Information Systems 202
- Management Science and Operations Research 103
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 0 | |
| 3 | 2021 | 2 | |
| 4 | Normalizing Kalman Filters for Multivariate Time Series Analysis | 2020 | 44 |
| 5 | BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations. | 2020 | 1 |
| 6 | 2019 | 2 | |
| 7 | Conditional Generative Adversarial Networks for Regression | 2019 | 6 |
| 8 | 2018 | 10 | |
| 9 | LIP6@CLEF2017: Multi-Modal Spatial Role Labeling using Word Embeddings. | 2017 | 1 |
| 10 | 2017 | 36 | |
| 11 | 2015 | 9 | |
| 12 | Extended Recommendation Framework: Generating the Text of a User Review as a Personalized Summary | 2014 | 6 |
| 13 | 2006 | 1 | |
| 14 | Boosting weak ranking functions to enhance passage retrieval for Question Answering | 2004 | 5 |
| 15 | Un modèle de mixture de modèles génératifs pour les documents structurés multimédias | 2004 | 1 |
| 16 | 1999 | 185 | |
| 17 | Modular neural net systems, training of | 1998 | 14 |
| 18 | 1997 | 4 | |
| 19 | A Framework for the Cooperation of Learning Algorithms | 1990 | 29 |
| 20 | 1987 | 19 |
About Patrick Gallinari
Patrick Gallinari is a scholar working on Artificial Intelligence, Computational Mathematics, Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 88 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural Networks and Applications (21 papers), Topic Modeling (17 papers), Natural Language Processing Techniques (15 papers), Text and Document Classification Technologies (12 papers), Speech Recognition and Synthesis (10 papers), Advanced Graph Neural Networks (9 papers), Speech and Audio Processing (6 papers) and Recommender Systems and Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (726 citations), Signal Processing (201 citations), Computer Vision and Pattern Recognition (242 citations), Information Systems (202 citations) and Management Science and Operations Research (103 citations). Patrick Gallinari has collaborated with scholars based in France, China and United States. Frequent co-authors include Ludovic Denoyer, C. Geourjon, Yann Guermeur, Philippe Leray, Sylvie Thiria, Françoise Fogelman‐Soulié, Benjamin Piwowarski, F. Badran, Françoise Fogelman Soulié and Sheng Gao. Their work appears in journals such as Machine Learning, Neurocomputing, Information Processing & Management, Knowledge and Information Systems and ACM SIGIR Forum.
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.