Temporal integration of auxin information for the regulation of patterning CS Galvan-Ampudia, G Cerutti, J Legrand, G Brunoud, R Martin-Arevalillo, ... Elife 9, e55832, 2020 | 108 | 2020 |
Piecewise deterministic Markov process—recent results R Azaïs, JB Bardet, A Génadot, N Krell, PA Zitt Esaim: Proceedings 44, 276-290, 2014 | 79 | 2014 |
Non‐parametric estimation of the conditional distribution of the interjumping times for piecewise‐deterministic Markov processes R Azaïs, F Dufour, A Gégout‐Petit Scandinavian Journal of Statistics 41 (4), 950-969, 2014 | 30 | 2014 |
Stochastic modelling and prediction of fatigue crack propagation using piecewise-deterministic Markov processes A Ben Abdessalem, R Azaïs, M Touzet-Cortina, A Gégout-Petit, ... Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2016 | 28 | 2016 |
Optimal quantization applied to sliced inverse regression R Azaïs, A Gégout-Petit, J Saracco Journal of Statistical Planning and Inference 142 (2), 481-492, 2012 | 26 | 2012 |
A recursive nonparametric estimator for the transition kernel of a piecewise-deterministic Markov process∗ R Azaïs ESAIM: Probability and Statistics 18, 726-749, 2014 | 17 | 2014 |
Nonparametric estimation of the jump rate for non-homogeneous marked renewal processes R Azaïs, F Dufour, A Gégout-Petit Annales de l'IHP Probabilités et statistiques 49 (4), 1204-1231, 2013 | 17 | 2013 |
A hidden renewal model for monitoring aquatic systems biosensors R Azaïs, R Coudret, G Durrieu Environmetrics 25 (3), 189-199, 2014 | 15 | 2014 |
The weight function in the subtree kernel is decisive R Azaïs, F Ingels Journal of Machine Learning Research 21, 2020 | 13 | 2020 |
Optimal choice among a class of nonparametric estimators of the jump rate for piecewise-deterministic Markov processes R Azaïs, A Muller-Guedin Electronic Journal of Statistics 10, 3648-3692, 2016 | 13 | 2016 |
Semi-parametric inference for the absorption features of a growth-fragmentation model R Azaïs, A Genadot Test 24 (2), 341-360, 2015 | 11 | 2015 |
Treex: a Python package for manipulating rooted trees R Azaïs, G Cerutti, D Gemmerlé, F Ingels Journal of Open Source Software 4 (38), 1351, 2019 | 10 | 2019 |
Transferring PointNet++ segmentation from virtual to real plants A Chaudhury, P Hanappe, R Azaïs, C Godin, D Colliaux ICCV 2021-International Conference on Computer Vision, 1-3, 2021 | 8 | 2021 |
Approximation of trees by self-nested trees R Azaïs, JB Durand, C Godin 2019 proceedings of the twenty-first workshop on algorithm engineering and …, 2019 | 7* | 2019 |
Statistical inference for piecewise-deterministic Markov processes R Azais, F Bouguet John Wiley & Sons, 2018 | 7 | 2018 |
Inference for conditioned Galton-Watson trees from their Harris path R Azaïs, A Genadot, B Henry Latin American Journal of Probability and Mathematical Statistics 16, 561-604, 2016 | 7 | 2016 |
Integral estimation based on Markovian design R Azaïs, B Delyon, F Portier Advances in Applied Probability 50 (3), 833-857, 2018 | 6 | 2018 |
Nearest embedded and embedding self-nested trees R Azaïs Algorithms 12 (9), 180, 2019 | 5 | 2019 |
Optimal choice among a class of nonparametric estimators of the jump rate for piecewise-deterministic Markov processes R Azaıs, A Muller-Guedin Electronic Journal of Statistics 10, 3648-3692, 2016 | 5 | 2016 |
Estimation, simulation et prévision d’un modèle de propagation de fissures par des processus markoviens déterministes par morceaux R Azaïs, C Elegbede, A Gégout-Petit, M Touzet 17ème Congrès Lambda-Mu, La Rochelle (France) 47, 2010 | 5 | 2010 |