nicolas brunel
nicolas brunel
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Cited by
Cited by
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
Parameter estimation of ODE’s via nonparametric estimators
NJB Brunel
Unsupervised signal restoration using hidden Markov chains with copulas
N Brunel, W Pieczynski
Signal processing 85 (12), 2304-2315, 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
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
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
The shapley value of coalition of variables provides better explanations
SI Amoukou, NJB Brunel, T Salaün
arXiv preprint arXiv:2103.13342, 2021
Unsupervised signal restoration using copulas and pairwise Markov chains
N Brunel, W Pieczynski
IEEE Workshop on Statistical Signal Processing, 2003, 102-105, 2003
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
A tracking approach to parameter estimation in linear ordinary differential equations
NJB Brunel, Q Clairon
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
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
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
Adaptive conformal prediction by reweighting nonconformity score
SI Amoukou, NJB Brunel
arXiv preprint arXiv:2303.12695, 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
The frenet-serret framework for aligning geometric curves
NJB Brunel, J Park
Geometric Science of Information: 4th International Conference, GSI 2019 …, 2019
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
Curvature and Torsion estimation of 3D functional data: A geometric approach to build the mean shape under the Frenet Serret framework
J Park, N Brunel, P Chassat
arXiv preprint arXiv:2203.02398, 2022
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
Removing phase variability to extract a mean shape for juggling trajectories
NJB Brunel, J Park
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