| Componentwise approximate Bayesian computation via Gibbs-like steps G Clarté, CP Robert, RJ Ryder, J Stoehr Biometrika 108 (3), 591-607, 2021 | 28 | 2021 |
| Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields J Stoehr, N Friel Artificial Intelligence and Statistics, 921-929, 2015 | 22 | 2015 |
| A review on statistical inference methods for discrete Markov random fields J Stoehr arXiv preprint arXiv:1704.03331, 2017 | 20 | 2017 |
| Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields J Stoehr, P Pudlo, L Cucala Statistics and Computing 25, 129-141, 2015 | 19* | 2015 |
| Faster Hamiltonian Monte Carlo by learning leapfrog scale C Wu, J Stoehr, CP Robert arXiv preprint arXiv:1810.04449, 2018 | 18 | 2018 |
| Noisy Hamiltonian Monte Carlo for doubly intractable distributions J Stoehr, A Benson, N Friel Journal of Computational and Graphical Statistics 28 (1), 220-232, 2019 | 11 | 2019 |
| Hidden Gibbs random fields model selection using block likelihood information criterion J Stoehr, JM Marin, P Pudlo Stat 5 (1), 158-172, 2016 | 8 | 2016 |
| GiRaF: a toolbox for Gibbs Random Fields analysis J Stoehr, P Pudlo, N Friel R package version 1 (1), 2020 | 4 | 2020 |
| Méthodes de Monte Carlo J STOEHR UNIVERSITÉ PARIS DAUPHINE, Département MIDO Master 1, 2019-2020, 2020 | 4 | 2020 |
| Statistical inférence methods for Gibbs random fields J Stoehr HAL 2015, 2015 | 2 | 2015 |
| Composite likelihood inference for the Poisson log-normal model J Stoehr, SS Robin arXiv preprint arXiv:2402.14390, 2024 | 1 | 2024 |
| Simulating signed mixtures J Stoehr, CP Robert arXiv preprint arXiv:2401.16828, 2024 | | 2024 |
| Méthodes d'inférence statistique pour champs de Gibbs J Stoehr Université Montpellier, 2015 | | 2015 |
| Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields L Cucala, J Stoehr, P Pudlo HAL 2015, 2015 | | 2015 |
| Poisson lognormal models for count data J Chiquet, M Mariadassou, S Robin, B Batardière, J Kwon, J Stoehr | | |
| Component-wise Approximate Bayesian Computation via Gibbs-like steps CPR GRegoire CLARTe, RJ RYDER, J STOEHR | | |
| A toolbox for Gibbs Random Fields analysis J Stoehr, P Pudlo, N Friel | | |
| Criteres de choix de modele pour champs de Gibbs cachés J Stoehr, JM Marin, P Pudlo | | |
| Statistiques résumées géométriques pour le choix de modele ABC entre des champs de Gibbs cachés J Stoehr, P Pudlo, L Cucala | | |
Pierre PudloAix-Marseille University; Institut de Mathématiques de Marseille (I2M)Verified email at univ-amu.fr
