François Fouss
-
- Complex Network Analysis Techniques 15
- Artificial Intelligence top 2%
- Advanced Graph Neural Networks 5
- Reinforcement Learning in Robotics 3
- Information Systems top 2%
- Recommender Systems and Techniques 7
- Web Data Mining and Analysis 3
-
- Data Management and Algorithms 6
-
- Advanced Bandit Algorithms Research 5
-
- Consumer Market Behavior and Pricing 3
In The Last Decade
François Fouss
32 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Statistical and Nonlinear Physics 632
- Artificial Intelligence 726
- Information Systems 429
- Computer Vision and Pattern Recognition 248
- Computational Mathematics 6
Countries citing papers authored by François Fouss
This map shows the geographic impact of François Fouss'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 François Fouss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites François Fouss more than expected).
Fields of papers citing papers by François Fouss
This network shows the impact of papers produced by François Fouss. 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 François Fouss. The network helps show where François Fouss may publish in the future.
Co-authorship network
The 13 scholars most cited alongside François Fouss, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2022 | 21 | |
| 4 | 2021 | 3 | |
| 5 | 2021 | 3 | |
| 6 | 2018 | 0 | |
| 7 | 2016 | 54 | |
| 8 | Improving accuracy by reducing the importance of hubs in nearest-neighbor recommendations | 2014 | 0 |
| 9 | 2012 | 83 | |
| 10 | 2010 | 17 | |
| 11 | 2010 | 16 | |
| 12 | 2008 | 13 | |
| 13 | 2008 | 27 | |
| 14 | Tuning Continual Exploration in Reinforcement Learning | 2007 | 4 |
| 15 | Optimal Tuning of Continual Online Exploration in Reinforcement Learning | 2006 | 7 |
| 16 | A novel way of computing similarities between nodes of a graph, with application to collaborative filtering and subspace projection of the graph nodes | 2006 | 17 |
| 17 | Clustering using a random walk based distance measure | 2005 | 52 |
| 18 | 2005 | 48 | |
| 19 | 2005 | 4 | |
| 20 | 2004 | 4 |
About François Fouss
François Fouss is a scholar working on Statistical and Nonlinear Physics, Management Science and Operations Research and Signal Processing, having authored 37 papers that have together received 1.5k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (15 papers), Recommender Systems and Techniques (7 papers), Data Management and Algorithms (6 papers), Advanced Bandit Algorithms Research (5 papers), Advanced Graph Neural Networks (5 papers), Web Data Mining and Analysis (3 papers), Reinforcement Learning in Robotics (3 papers) and Consumer Market Behavior and Pricing (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (632 citations), Artificial Intelligence (726 citations) and Information Systems (429 citations). François Fouss has collaborated with scholars based in Belgium, Japan and France. Frequent co-authors include Marco Saerens, Alain Pirotte, Jean-Michel Renders, Luh Yen, Masashi Shimbo, Christine Decaestecker, Michel Verleysen, Fabian Lecron, Ivan Jureta and Amin Mantrach.
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.