| Variable selection using random forests R Genuer, JM Poggi, C Tuleau-Malot Pattern recognition letters 31 (14), 2225-2236, 2010 | 2618 | 2010 |
| VSURF: an R package for variable selection using random forests R Genuer, JM Poggi, C Tuleau-Malot The R Journal 7 (2), 19-33, 2015 | 556 | 2015 |
| Random forests for big data R Genuer, JM Poggi, C Tuleau-Malot, N Villa-Vialaneix Big Data Research 9, 28-46, 2017 | 335 | 2017 |
| Inference of functional connectivity in neurosciences via Hawkes processes P Reynaud-Bouret, V Rivoirard, C Tuleau-Malot 2013 IEEE global conference on signal and information processing, 317-320, 2013 | 120 | 2013 |
| Goodness-of-fit tests and nonparametric adaptive estimation for spike train analysis P Reynaud-Bouret, V Rivoirard, F Grammont, C Tuleau-Malot The Journal of Mathematical Neuroscience 4, 1-41, 2014 | 110 | 2014 |
| Reconstructing the functional connectivity of multiple spike trains using Hawkes models RC Lambert, C Tuleau-Malot, T Bessaih, V Rivoirard, Y Bouret, ... Journal of neuroscience methods 297, 9-21, 2018 | 57 | 2018 |
| Adaptive density estimation: a curse of support? P Reynaud-Bouret, V Rivoirard, C Tuleau-Malot Journal of Statistical Planning and Inference 141 (1), 115-139, 2011 | 56 | 2011 |
| VSURF: Variable selection using random forests R Genuer, JM Poggi, C Tuleau-Malot R package version 1 (0), 2019 | 43 | 2019 |
| Multiple tests based on a gaussian approximation of the unitary events method with delayed coincidence count C Tuleau-Malot, A Rouis, F Grammont, P Reynaud-Bouret Neural computation 26 (7), 1408-1454, 2014 | 27 | 2014 |
| Package ‘vsurf’ R Genuer, JM Poggi, C Tuleau-Malot, MR Genuer Pattern Recognition Letters 31 (14), 2225-2236, 2019 | 18 | 2019 |
| Variable selection through CART M Sauvé, C Tuleau-Malot arXiv preprint arXiv:1101.0689, 2011 | 12 | 2011 |
| Spike trains as (in) homogeneous Poisson processes or Hawkes processes: non-parametric adaptive estimation and goodness-of-fit tests P Reynaud-Bouret, C Tuleau-Malot, V Rivoirard, F Grammont Journal of Mathematical Neuroscience 39 (8), 32-33, 2013 | 11 | 2013 |
| A model of Poissonian interactions and detection of dependence L Sansonnet, C Tuleau-Malot Statistics and Computing 25, 449-470, 2015 | 10 | 2015 |
| Variable selection through CART∗ M Sauve, C Tuleau-Malot ESAIM: Probability and Statistics 18, 770-798, 2014 | 8 | 2014 |
| Multiple tests based on a Gaussian approximation of the unitary events method C Tuleau-Malot, A Rouis, P Reynaud-Bouret, F Grammont | 4 | 2012 |
| Completeness period analysis of SisFrance macroseismic database and interpretation in the light of historical context J Bonnet, T Fradet, P Traversa, C Tuleau-Malot, P Reynaud-Bouret, ... EGU General Assembly Conference Abstracts, 12118, 2014 | 1 | 2014 |
| Sélection de variables par forêts aléatoires C Tuleau-Malot | | 2016 |
| Random Forests for Big Data N Villa-Vialaneix, R Genuer, JM Poggi, C Tuleau-Malot Journées de Statistique de Rennes (JSTAR), 2016 | | 2016 |
| VSURF: un package R pour la sélection de variables à l'aide de forêts aléatoires R Genuer, JM Poggi, C Tuleau-Malot 46èmes Journées de Statistique, 2014 | | 2014 |
| Comment les statisticiens peuvent aidera une meilleure compréhension de l’activité neuronale? F Grammont, P Reynaud-Bouret, A Rouis, C Tuleau-Malot | | |
