Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference M Quach, N Brunel, F d'Alché-Buc Bioinformatics 23 (23), 3209-3216, 2007 | 197 | 2007 |
Parameter estimation of ODE’s via nonparametric estimators NJB Brunel | 181 | 2008 |
Unsupervised signal restoration using hidden Markov chains with copulas N Brunel, W Pieczynski Signal processing 85 (12), 2304-2315, 2005 | 64 | 2005 |
Parametric estimation of ordinary differential equations with orthogonality conditions NJB Brunel, Q Clairon, F d’Alché-Buc Journal of the American Statistical Association 109 (505), 173-185, 2014 | 43 | 2014 |
Copulas in vectorial hidden Markov chains for multicomponent image segmentation N Brunel, W Pieczynski, S Derrode Proceedings.(ICASSP'05). IEEE International Conference on Acoustics, Speech …, 2005 | 33 | 2005 |
Modeling and unsupervised classification of multivariate hidden Markov chains with copulas NJB Brunel, J Lapuyade-Lahorgue, W Pieczynski IEEE Transactions on Automatic Control 55 (2), 338-349, 2009 | 27 | 2009 |
The shapley value of coalition of variables provides better explanations SI Amoukou, NJB Brunel, T Salaün arXiv preprint arXiv:2103.13342, 2021 | 21* | 2021 |
Unsupervised signal restoration using copulas and pairwise Markov chains N Brunel, W Pieczynski IEEE Workshop on Statistical Signal Processing, 2003, 102-105, 2003 | 19 | 2003 |
A tracking approach to parameter estimation in linear ordinary differential equations NJB Brunel, Q Clairon | 12 | 2015 |
Humans are able to self-paced constant running accelerations until exhaustion V Billat, NJB Brunel, T Carbillet, S Labbé, A Samson Physica A: Statistical Mechanics and its Applications 506, 290-304, 2018 | 10 | 2018 |
Sur quelques extensions des chaînes de Markov cachées et couples. Applications à la segmentation non-supervisée de signaux radar. N Brunel Université Pierre et Marie Curie-Paris VI, 2005 | 10 | 2005 |
Consistent sufficient explanations and minimal local rules for explaining the decision of any classifier or regressor S I Amoukou, N Brunel Advances in Neural Information Processing Systems 35, 8027-8040, 2022 | 9* | 2022 |
MAPIE: an open-source library for distribution-free uncertainty quantification V Taquet, V Blot, T Morzadec, L Lacombe, N Brunel arXiv preprint arXiv:2207.12274, 2022 | 9 | 2022 |
Doppler and polarimetric statistical segmentation for radar clutter map based on pairwise Markov chains N Brunel, F Barbaresco Proc. of IEEE RADAR, 10-8, 2007 | 6 | 2007 |
Adaptive conformal prediction by reweighting nonconformity score SI Amoukou, NJB Brunel arXiv preprint arXiv:2303.12695, 2023 | 5 | 2023 |
Tracking for parameter and state estimation in possibly misspecified partially observed linear ordinary differential equations Q Clairon, NJB Brunel Journal of Statistical Planning and Inference 199, 188-206, 2019 | 5 | 2019 |
The frenet-serret framework for aligning geometric curves NJB Brunel, J Park Geometric Science of Information: 4th International Conference, GSI 2019 …, 2019 | 5 | 2019 |
Optimal control and additive perturbations help in estimating ill-posed and uncertain dynamical systems Q Clairon, NJB Brunel Journal of the American Statistical Association 113 (523), 1195-1209, 2018 | 5 | 2018 |
Removing phase variability to extract a mean shape for juggling trajectories NJB Brunel, J Park | 5 | 2014 |
Copulas in vectorial hidden Markov chains for multicomponent image classification N Brunel, W Piezcynski, S Derrode IEEE Internat. Conf. on Acoustics, Speech and Signal Processing, 2005 | 5 | 2005 |