| Mobility-based SIR model for complex networks: with case study Of COVID-19 R Goel, L Bonnetain, R Sharma, A Furno Social Network Analysis and Mining 11 (1), 1-18, 2021 | 56 | 2021 |
| Spatio-temporal Correlations of Betweenness Centrality and Traffic Metrics E Henry, L Bonnetain, A Furno, NE El Faouzi, E Zimeo IEEE International Conference on Models and Technologies for Intelligent …, 2019 | 36 | 2019 |
| TRANSIT: Fine-grained human mobility trajectory inference at scale with mobile network signaling data L Bonnetain, A Furno, NE El Faouzi, M Fiore, R Stanica, Z Smoreda, ... Transportation Research Part C: Emerging Technologies 130, 103257, 2021 | 34 | 2021 |
| Constructing Spatiotemporal Load Profiles of Transit Vehicles with Multiple Data Sources D Luo, L Bonnetain, O Cats, H Van Lint Transportation Research Record, 0361198118781166, 2018 | 28 | 2018 |
| Can We Map-Match Individual Cellular Network Signaling Trajectories in Urban Environments? Data-Driven Study L Bonnetain, A Furno, J Krug, NEE Faouzi Transportation Research Record, 0361198119847472, 2019 | 19 | 2019 |
| Potential of cellular signaling data for time-of-day estimation and spatial classification of travel demand: a large-scale comparative study with travel survey and land use data M Fekih, L Bonnetain, A Furno, P Bonnel, Z Smoreda, S Galland, ... Transportation Letters, 1-19, 2021 | 15 | 2021 |
| Unlocking the potential of mobile phone data for large scale urban mobility estimation L Bonnetain Université de Lyon, 2022 | 1 | 2022 |
| A Lightweight Approach for Origin-Destination Matrix Anonymization. B Matet, E Côme, A Furno, L Bonnetain, L Oukhellou, NE El Faouzi ESANN, 2021 | | 2021 |
| Assessing the potential of cellular signaling data to generate dynamic travel patterns: A comparative study with travel survey data M FEKIH, T BELLEMANS, A Furno, L Bonnetain, P Bonnel, Z Smoreda, ... | | 2020 |
