| Expectation propagation in the large data limit G Dehaene, S Barthelmé Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2018 | 59 | 2018 |
| Bounding errors of expectation-propagation GP Dehaene, S Barthelmé Advances in Neural Information Processing Systems, 244-252, 2015 | 32 | 2015 |
| Investigating the representation of uncertainty in neuronal circuits GP Dehaene, R Coen-Cagli, A Pouget PLoS computational biology 17 (2), e1008138, 2021 | 14 | 2021 |
| Outlier detection and rejection in scatterplots: Do outliers influence intuitive statistical judgments? L Ciccione, G Dehaene, S Dehaene Journal of Experimental Psychology: Human Perception and Performance 49 (1), 129, 2023 | 12 | 2023 |
| A deterministic and computable Bernstein-von Mises theorem G Dehaene arXiv preprint arXiv:1904.02505, 2019 | 12 | 2019 |
| Computing the quality of the Laplace approximation GP Dehaene arXiv preprint arXiv:1711.08911, 2017 | 5 | 2017 |
| Expectation Propagation performs a smoothed gradient descent GP Dehaene arXiv preprint arXiv:1612.05053, 2016 | 1 | 2016 |
| Weber's law and natural inference J Beck, I Kanitscheider, G Dehaene, A Pouget bioRxiv, 2024.08. 10.607448, 2024 | | 2024 |
| Variational Inference with Numerical Derivatives: variance reduction through coupling A Immer, GP Dehaene arXiv preprint arXiv:1906.06914, 2019 | | 2019 |
| Expectation propagation in the large data limit Series B Statistical methodology G Dehaene, S Barthelmé | | 2018 |
Simon BarthelméCNRS Research Fellow, Gipsa-labVerified email at gipsa-lab.fr
