| A random forest guided tour G Biau, E Scornet Test 25 (2), 197-227, 2016 | 4088 | 2016 |
| Analysis of a random forests model G Biau The Journal of Machine Learning Research 13, 1063-1095, 2012 | 2110 | 2012 |
| Consistency of random forests and other averaging classifiers. G Biau, L Devroye, G Lugosi Journal of Machine Learning Research 9 (9), 2008 | 823 | 2008 |
| Consistency of random forests E Scornet, G Biau, JP Vert | 741 | 2015 |
| Lectures on the nearest neighbor method G Biau, L Devroye Springer, 2015 | 374 | 2015 |
| Functional classification in Hilbert spaces G Biau, F Bunea, MH Wegkamp IEEE Transactions on Information Theory 51 (6), 2163-2172, 2005 | 208 | 2005 |
| On the performance of clustering in Hilbert spaces G Biau, L Devroye, G Lugosi IEEE Transactions on Information Theory 54 (2), 781-790, 2008 | 191 | 2008 |
| On the layered nearest neighbour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification G Biau, L Devroye Journal of Multivariate Analysis 101 (10), 2499-2518, 2010 | 177 | 2010 |
| Accelerated gradient boosting G Biau, B Cadre, L Rouvìère Machine learning 108, 971-992, 2019 | 159 | 2019 |
| Supervised reconstruction of biological networks with local models K Bleakley, G Biau, JP Vert Bioinformatics 23 (13), i57-i65, 2007 | 147 | 2007 |
| Estimation of precipitation by kriging in the EOF space of thesea level pressure field G Biau, E Zorita, H von Storch, H Wackernagel Journal of climate 12 (4), 1070-1085, 1999 | 146 | 1999 |
| Neural random forests G Biau, E Scornet, J Welbl Sankhya A 81 (2), 347-386, 2019 | 143 | 2019 |
| New insights into approximate Bayesian computation G Biau, F Cérou, A Guyader Annales de l'IHP Probabilités et statistiques 51 (1), 376-403, 2015 | 141 | 2015 |
| Nonparametric spatial prediction G Biau, B Cadre Statistical Inference for Stochastic Processes 7, 327-349, 2004 | 124 | 2004 |
| Sparse single-index model. P Alquier, G Biau Journal of Machine Learning Research 14 (1), 2013 | 118 | 2013 |
| Probability estimation with machine learning methods for dichotomous and multicategory outcome: theory J Kruppa, Y Liu, G Biau, M Kohler, IR König, JD Malley, A Ziegler Biometrical Journal 56 (4), 534-563, 2014 | 113 | 2014 |
| On the Rate of Convergence of the Bagged Nearest Neighbor Estimate. G Biau, F Cérou, A Guyader Journal of Machine Learning Research 11 (2), 2010 | 106 | 2010 |
| A weighted k-nearest neighbor density estimate for geometric inference G Biau, F Chazal, D Cohen-Steiner, L Devroye, C Rodriguez | 97 | 2011 |
| Interpretable random forests via rule extraction C Bénard, G Biau, S Da Veiga, E Scornet International conference on artificial intelligence and statistics, 937-945, 2021 | 92 | 2021 |
| Rates of Convergence of the Functional -Nearest Neighbor Estimate G Biau, F Cérou, A Guyader IEEE Transactions on Information Theory 56 (4), 2034-2040, 2010 | 80 | 2010 |
