Preprints

• Pelletier, B. (2024). On the statistical properties of the isolation forest anomaly detection method.

Journal papers

• Arias-Castro, E., Channarond, A., Pelletier, B. and Verzelen, N. (2021). On the estimation of latent distances using graph distances. Electronic Journal of Statistics, Vol. 15, No. 1, pp. 722-747.
• Arias-Castro, E., Javanmard, A. and Pelletier, B. (2020). Perturbation bounds for Procrustes,classical scaling and trilateration, with applications to manifold learning. Journal of Machine Learning Research, Vol. 21, pp. 1-37.
• Frouin R., Franz B., Ibrahim A., Knobelspiesse K., Ahmad Z., Cairns B., Chowdhary J., Dierssen H., Tan J., Dubovik O., Huang X., Davis A., Kalashnikova O., Thompson D., Remer L., Boss E., Coddington O., Deschamps P.-Y., Gao B., Gross L., Hasekamp O., Omar A., Pelletier B., Ramon D., Steinmetz F., Zhai P.-W. (2019). Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era. Frontiers in Earth Science, Vol. 7, doi=10.3389/feart.2019.00145.
• Mason, D. and Pelletier, B. (2019). Uniform in bandwidth estimation of the gradient lines of a density. High Dimensional Probability VIII, pp. 431-455.
• Arias-Castro, E., Pelletier, B. and Saligrama, V. (2018). Remember the curse of dimensionality: The case of goodness-of-fit testing in arbitrary dimension. Journal of Nonparametric Statsitics, Vol. 30(2), pp. 448-471.
• Del Barrio, E., Loubes, J.-M. and Pelletier, B. (2017) An inverse problem: Recovery of a distribution using Wasserstein barycenter. Annals of Economics and Statistics, No. 128, pp. 229-259.
• Loubes, J.-M. and Pelletier, B. (2017). Prediction by quantization of a conditional distribution. Electronic Journal of Statistics, Vol. 11, No. 1, pp. 2679-2706.
• Arias-Castro, E. and Pelletier, B. (2016) On the consistency of the crossmatch test. Journal of Statistical Planning and Inference, Vol. 171, pp. 184-190.
• Arias-Castro, E., Mason, D. and Pelletier, B. (2016) On the estimation of the gradient lines of a density and the consistency of the mean-shift algorithm. Journal of Machine Learning Research, Vol. 17(43), pp. 1-28. Errata.
• Frouin, R. and Pelletier, B. (2015). Bayesian methodology for inverting satellite ocean color data. Remote Sensing of Environment, Vol. 159, pp.332-360.
• Arias-Castro, E. and Pelletier, B. (2013). On the convergence of maximum variance unfolding. Journal of Machine Learning Research, Vol. 14, pp. 1747-1770.
• Cadre, B., Pelletier, B. and Pudlo, P. (2013). Estimation of density level sets with a given probability content. Journal of Nonparametric Statistics, Vol. 25, No. 1, pp. 261-272.
• Arias-Castro, E., Pelletier, B., and Pudlo, P. (2012). The normalized graph cut and Cheeger constant: from discrete to continuous. Advances in Applied Probability, Vol. 44, pp. 907-937.
• Pelletier, B. and Pudlo, B. (2011). Operator norm convergence of spectral clustering on level sets. Journal of Machine Learning Research, Vol. 12, pp.385-416.
• Pelletier, B. (2011). Inference in phi-families of distributions. Statistics, Vol. 45, pp. 223-236.
• Biau, G., Cadre, B., Mason, D., and Pelletier, B. (2009). Asymptotic normality in density support estimation. Electronic Journal of Probability, Vol. 14, pp. 2617-2635.
• Frouin, R. and Pelletier, B. (2009). Consistency of ridge function fields for varying nonparametric regession. Communications in Statistics: Theory and Methods, Vol. 38, No. 8, pp. 1272-1283.
• Frouin, R. and Pelletier, B. (2009). Function field methodology for estimating spectral marine reflectance from ADEOS-II global imager data. Journal of the Remote Sensing Society of Japan, Vol. 29, No. 1, pp. 86-95.
• Loubes, J.-M. and Pelletier, B. (2008). A kernel-based classifier on a Riemannian manifold. Statistics and Decisions, Vol. 26, No. 1, pp. 35-51.
• Loubes, J.-M; and Pelletier, B. (2008). Approximate maximum entropy solution to ill-posed inverse problems with approximately known operator. Journal of Mathematical Analysis and Applications, Vol. 344, pp. 260-273.
• Biau, G., Cadre, B., and Pelletier, B. (2008). Exact rates in density support estimation. Journal of Multivariate Analysis, Vol. 99, No. 10, pp. 2185-2207.
• Frouin, R. and Pelletier, B. (2007). Fields of nonlinear regression models for atmospheric correction of satellite ocean-color imagery. Remote Sensing of the Environment, Vol. 111, No. 4, pp. 450-465.
• Biau, G., Cadre, B. and Pelletier, B. (2007). A graph-based estimator of the number of clusters. ESAIM: Probability and Statistics, Vol. 11, pp. 272-280.
• Pelletier, B., Santer, R. and Vidot, J. (2007). Retrieving of particulate matter from optical measurements: A semiparametric approach. Journal of Geophysical Research - Atmospheres, Vol. 112, doi: 10.1029/2005JD06737.
• Pelletier, B. (2006). Nonparametric regression estimation on closed Riemannian manifolds. Journal of Nonparametric Statistics, Vol. 18, No. 1, pp. 57-67.
• Pelletier, B. and Frouin, R. (2006). Remote sensing of phytoplankton chlorophyll-a concentration by use of ridge function fields. Applied Optics, Vol. 45, No. 4, pp. 784-798.
• Pelletier, B. (2005). Informative barycentres in statistics. Annals of the Institute of Statistical Mathematics, Vol. 57, No. 4, pp. 767-780.
• Pelletier, B. (2005). Kernel density estimation on Riemannian manifolds. Statistics and Probability Letters, Vol. 73, No. 3, pp. 297-304.
• Pelletier, B. (2004). Approximation by ridge function fields over compact sets. Journal of Approximation theory, Vol. 129, No. 2, pp. 230-239.
• Pelletier, B. and Frouin, R. (2004). Fields of nonlinear regression models for inversion of satellite data. Geophysical Research Letters, Vol. 31, L16304, doi 10.1029/2004GL019840.

Conference Proceedings

• Frouin, R. and Pelletier, B. (2010). Statistical inference in remote sensing of ocean color, In Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment, Proceedings of SPIE, Vol. 7858, doi:10.1117/12.870677.
• Frouin, R. and Pelletier, B. (2010). A statistical model of marine reflectance, In Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment, Proceedings of SPIE, Vol. 7858, doi: 10.1117/12.870683.
• Frouin, R. and Pelletier, B. (2009). Noise and model uncertainties in ocean color remote sensing, In Ocean Remote Sensing: Methods and Applications, Proceedings of SPIE, Vol. 7459, doi: 10.1117/12.829794.
• Pelletier, B., Frouin, R. and Dubuisson, P. (2008), Retrieval of the aerosol vertical distribution from atmospheric radiance, In Remote Sensing of Inland, Coastal, and Oceanic Waters, Proceedings of SPIE, Vol. 7150, doi:10.1117/12.806527.
• Pelletier, B., Frouin, R. and Dubuisson, P. (2007), Maximum entropy regularization for inferring aerosol vertical distribution from light scattering measurements, In Coastal Ocean Remote Sensing, Proceedings of SPIE, Vol. 6680, doi:10.1117/12.738168.
• Frouin, R. and Pelletier, B. (2007), Constrained linear inversion of ocean-color data, In Coastal Ocean Remote Sensing, Proceedings of SPIE, Vol. 6680, doi:10.1117/12.738690.
• Frouin, R. and Pelletier, B. (2006), A stochastic technique for remote sensing of ocean color, In Remote Sensing of the Marine Environment, Proceedings of SPIE, Vol. 6406, pp. 02.1-12.
• Frouin, R. Gross, L., and Pelletier, B. (2006), Progressive atmospheric correction of satellite ocean-color imagery, In Remote Sensing of the Marine Environment, Proceedings of SPIE, Vol. 6406, pp. 1S.1-12.
• Pelletier, B. and R. Frouin (2004), Function Field Methodology for Estimation of Ocean Color Variables from Space, Ocean Optics XVII, Fremantle, Australia, 25-29 October, 2004, 8 pages on CD-ROM.
• Pelletier, B. and R. Frouin (2004), Fields of nonlinear regression models for ocean color remote sensing from space, In Active and Passive Remote Sensing of the Oceans, Proceedings of SPIE, Vol. 5656, pp. 21-32.
• Pelletier, B. and R. Frouin (2004), On fields of nonlinear regression models, In Proceedings of ESANN 2004, Bruges, Belgium, April 28-30, pp 187-192, 2004.
• Pelletier, B. (2003). Neural network fields, In Proceedings of the IEEE ICNNSP, Toulouse, France, 17-19 September 2003, pp. 167-176.
• Pelletier, B. (2002). Remote sensing of phytoplankton with neural networks, In Remote Sensing of the Ocean and Sea Ice, Proceedings of SPIE, Vol. 4880, pp. 158-169.
• Pelletier, B. (2002). Interpolation and approximation of models, In Proceedings of ICNNSC, Zakopane, Poland, 10-15 June 2002, pp. 716-721, Physica-Verlag.
• Bourret, P. and Pelletier, B. (2001). Curved kernel neural network for function approximation, In Proceedings of IWANN, Granada, Spain, 13-15 June 2001, Vol. 2, pp. 80-87, Springer-Verlag.