| Event-scheduling algorithms with Kalikow decomposition for simulating potentially infinite neuronal networks TC Phi, A Muzy, P Reynaud-Bouret arXiv preprint arXiv:1910.10576, 2019 | 9 | 2019 |
| A new progress on weak Dirac conjecture HH Pham, TC Phi arXiv preprint arXiv:1607.08398, 2016 | 5 | 2016 |
| Kalikow decomposition for counting processes with stochastic intensity and application to simulation algorithms TC Phi, E Löcherbach, P Reynaud-Bouret Journal of Applied Probability 60 (4), 1469-1500, 2023 | 4 | 2023 |
| Reconstruction de la connectivité fonctionnelle en Neurosciences: une amélioration des algorithmes actuels G Scarella, C Mascart, A Muzy, TC Phi, P Reynaud-Bouret 52èmes Journées de Statistique de la Société Française de Statistique (SFdS), 2021 | 1 | 2021 |
| Neural mechanisms of individual differences in prior weight during scene recognition TC Phi, K Hayashi, R Katayama, K Nakae, S Ishii NeuroImage, 121613, 2025 | | 2025 |
| Integrated information theory reveals the potential role of the posterior parietal cortex in sustaining conditioning responses in classical conditioning tasks TC Phi, S Ishii, M Kondo, M Matsuzaki, K Nakae Frontiers in Neuroscience 19, 1512724, 2025 | | 2025 |
| Kalikow decomposition for counting processes with stochastic intensity TC Phi Université Côte d'Azur, 2022 | | 2022 |
Patricia Reynaud-BouretUniversité Côte d’Azur, CNRS, LJAD, FranceVerified email at univ-cotedazur.fr
