| Mean field limits for nonlinear spatially extended Hawkes processes with exponential memory kernels J Chevallier, A Duarte, E Löcherbach, G Ost Stochastic Processes and their Applications 129 (1), 1-27, 2019 | 71 | 2019 |
| A model for neural activity in the absence of external stimuli A Duarte, G Ost Markov Processes And Related Fields, v.22, Issue 1, 37-52, 2016 | 51 | 2016 |
| Stability, convergence to equilibrium and simulation of non-linear Hawkes processes with memory kernels given by the sum of Erlang kernels A Duarte, E Löcherbach, G Ost ESAIM: Probability and Statistics 23, 770-796, 2019 | 46 | 2019 |
| Estimating the interaction graph of stochastic neural dynamics A Duarte, A Galves, E Löcherbach, G Ost Bernoulli 25(1): 771-792, 2019 | 34 | 2019 |
| Hydrodynamic limit for spatially structured interacting neurons A Duarte, G Ost, AA Rodríguez Journal of Statistical Physics 161 (5), 1163-1202, 2015 | 34 | 2015 |
| Sparse space–time models: Concentration inequalities and Lasso G Ost, P Reynaud-Bouret Ann. Inst. H. Poincaré Probab. Statist. 56(4): 2377-2405 56 (4), 2377-2405, 2020 | 21 | 2020 |
| Fluctuations for spatially extended Hawkes processes J Chevallier, G Ost Stochastic Processes and their Applications 130 (9), 5510-5542, 2020 | 14 | 2020 |
| Retrieving the structure of probabilistic sequences of auditory stimuli from eeg data N Hernández, A Duarte, G Ost, R Fraiman, A Galves, CD Vargas Scientific Reports 11 (1), 3520, 2021 | 12 | 2021 |
| Retrieving a context tree from eeg data A Duarte, R Fraiman, A Galves, G Ost, CD Vargas Mathematics 7 (5), 427, 2019 | 11 | 2019 |
| Statistical model selection for stochastic systems with applications to bioinformatics, linguistics and neurobiology A Galves, FG Leonardi, G Ost | 5 | 2022 |
| Community detection for binary graphical models in high dimension J Chevallier, G Ost arXiv preprint arXiv:2411.15627, 2024 | 4 | 2024 |
| Estimation of neuronal interaction graph from spike train data L Brochini, A Galves, P Hodara, G Ost, C Pouzat arXiv preprint arXiv:1612.05226, 2016 | 4 | 2016 |
| Sparse Markov models for high-dimensional inference G Ost, DY Takahashi Journal of Machine Learning Research 24 (279), 1-54, 2023 | 3 | 2023 |
| Neural coding as a statistical testing problem G Ost, P Reynaud-Bouret Mathematical Neuroscience and Applications 3, 2023 | 2 | 2023 |
| Inferring the dependence graph density of binary graphical models in high dimension J Chevallier, E Löcherbach, G Ost arXiv preprint arXiv:2406.07066, 2024 | 1 | 2024 |
| Self-switching markov chains: Emerging dominance phenomena S Gallo, G Iacobelli, G Ost, DY Takahashi Stochastic Processes and their Applications 143, 254-284, 2022 | 1 | 2022 |
| hdMTD: An R Package for High-Dimensional Mixture Transition Distribution Models M Gripp, G Iacobelli, G Ost, DY Takahashi arXiv preprint arXiv:2509.01808, 2025 | | 2025 |
| Self-switching random walks on Erdös–Rényi random graphs feel the phase transition G Iacobelli, G Ost, DY Takahashi Stochastic Processes and their Applications 183, 104589, 2025 | | 2025 |
