Nonlinear Modeling of Scattered Multivariate Data and Its Application to Shape Change. - Bernard Chalmond; Stéphane Girard (IEEE Trans. Pattern Anal. Mach. Intell., 1999)

A nonlinear PCA based on manifold approximation. - Stéphane Girard (Comput. Stat., 2000)

Le logiciel EXTREMES, un outil pour l'étude des queues de distribution. - Jean Diebolt; Jérôme Ecarnot; Myriam Garrido; Stéphane Girard; Dominique Lagrange (Monde des Util. Anal. Données, 2003)

Sliced inverse regression in reference curves estimation. - Ali Gannoun; Stéphane Girard; Christiane Guinot; Jérôme Saracco (Comput. Stat. Data Anal., 2004)

Implémentation en C d'estimateurs non paramétriques de quantiles conditionnels. Application au tracé de courbes de référence. - Ali Gannoun; Stéphane Girard; Christiane Guinot; Jérôme Saracco (Monde des Util. Anal. Données, 2004)

Class-Specific Subspace Discriminant Analysis for High-Dimensional Data. - Charles Bouveyron; Stéphane Girard; Cordelia Schmid (SLSFS, 2005)

Object Localization by Subspace Clustering of Local Descriptors. - Charles Bouveyron; Juho Kannala; Cordelia Schmid; Stéphane Girard (ICVGIP, 2006)

High-dimensional data clustering. - Charles Bouveyron; Stéphane Girard; Cordelia Schmid (Comput. Stat. Data Anal., 2007)

Inverting hyperspectral images with Gaussian Regularized Sliced Inverse Regression. - Caroline Bernard-Michel; Sylvain Douté; Laurent Gardes; Stéphane Girard (ESANN, 2008)

Support vectors machines regression for estimation of mars surface physical properties. - Caroline Bernard-Michel; Sylvain Douté; Mathieu Fauvel; Laurent Gardes; Stéphane Girard (ESANN, 2009)

Supervised classification of categorical data with uncertain labels for DNA barcoding. - Charles Bouveyron; Stéphane Girard; Madalina Olteanu (ESANN, 2009)

Maximum likelihood estimation of the flow size distribution tail index from sampled packet data. - Patrick Loiseau; Paulo Gonçalves 001; Stéphane Girard; Florence Forbes; Pascale Vicat-Blanc Primet (SIGMETRICS/Performance, 2009)

Machine learning techniques for the inversion of planetary hyperspectral images. - Caroline Bernard-Michel; Sylvain Douté; Mathieu Fauvel; Laurent Gardes; Stéphane Girard (WHISPERS, 2009)

Frontier estimation with local polynomials and high power-transformed data. - Stéphane Girard; Pierre Jacob (J. Multivar. Anal., 2009)

Classification supervisée et non supervisée en grande dimension. - Charles Bouveyron; Stéphane Girard (Monde des Util. Anal. Données, 2009)

Robust supervised classification with mixture models: Learning from data with uncertain labels. - Charles Bouveyron; Stéphane Girard (Pattern Recognit., 2009)

Gaussian Regularized Sliced Inverse Regression. - Caroline Bernard-Michel; Laurent Gardes; Stéphane Girard (Stat. Comput., 2009)

Functional nonparametric estimation of conditional extreme quantiles. - Laurent Gardes; Stéphane Girard; Alexandre Lekina (J. Multivar. Anal., 2010)

Intrinsic dimension estimation by maximum likelihood in isotropic probabilistic PCA. - Charles Bouveyron; Gilles Celeux; Stéphane Girard (Pattern Recognit. Lett., 2011)

Statistical Estimation of Dominant Physical Parameters for Leakage Variability in 32 Nanometer CMOS, Under Supply Voltage Variations. - Smriti Joshi; Anne Lombardot; Philippe Flatresse; Carmelo D'Agostino; Andre Juge; Edith Beigné; Stéphane Girard (J. Low Power Electron., 2012)

A gate level methodology for efficient statistical leakage estimation in complex 32nm circuits. - Smriti Joshi; Anne Lombardot; Marc Belleville; Edith Beigné; Stéphane Girard (DATE, 2013)

Frontier estimation with kernel regression on high order moments. - Stéphane Girard; Armelle Guillou; Gilles Stupfler (J. Multivar. Anal., 2013)

Parsimonious Gaussian process models for the classification of multivariate remote sensing images. - Mathieu Fauvel; Charles Bouveyron; Stéphane Girard (ICASSP, 2014)

L 1-optimal linear programming estimator for periodic frontier functions with Hölder continuous derivative. - Alexander V. Nazin; Stéphane Girard (Autom. Remote. Control., 2014)

A new sliced inverse regression method for multivariate response. - Raphaël Coudret; Stéphane Girard; Jérôme Saracco (Comput. Stat. Data Anal., 2014)

A sliced inverse regression approach for data stream. - Marie Chavent; Stéphane Girard; Vanessa Kuentz-Simonet; Benoit Liquet; Thi Mong Ngoc Nguyen; Jérôme Saracco (Comput. Stat., 2014)

Estimating Local Intrinsic Dimensionality. - Laurent Amsaleg; Oussama Chelly; Teddy Furon; Stéphane Girard; Michael E. Houle; Ken-ichi Kawarabayashi; Michael Nett (KDD, 2015)

Parsimonious Gaussian Process Models for the Classification of Hyperspectral Remote Sensing Images. - Mathieu Fauvel; Charles Bouveyron; Stéphane Girard (IEEE Geosci. Remote. Sens. Lett., 2015)

Nonparametric estimation of the conditional tail copula. - Laurent Gardes; Stéphane Girard (J. Multivar. Anal., 2015)

A class of multivariate copulas based on products of bivariate copulas. - Gildas Mazo; Stéphane Girard; Florence Forbes (J. Multivar. Anal., 2015)

Kernel discriminant analysis and clustering with parsimonious Gaussian process models. - Charles Bouveyron; Mathieu Fauvel; Stéphane Girard (Stat. Comput., 2015)

High dimensional Kullback-Leibler divergence for grassland management practices classification from high resolution satellite image time series. - Maïlys Lopes; Mathieu Fauvel; Stéphane Girard; David Sheeren (IGARSS, 2016)

Marshall-Olkin type copulas generated by a global shock. - Fabrizio Durante; Stéphane Girard; Gildas Mazo (J. Comput. Appl. Math., 2016)

On the estimation of the functional Weibull tail-coefficient. - Laurent Gardes; Stéphane Girard (J. Multivar. Anal., 2016)

A flexible and tractable class of one-factor copulas. - Gildas Mazo; Stéphane Girard; Florence Forbes (Stat. Comput., 2016)

Potential of Sentinel-2 and SPOT5 (Take5) time series for the estimation of grasslands biodiversity indices. - Maïlys Lopes; Mathieu Fauvel; Annie Ouin; Stéphane Girard (MultiTemp, 2017)

Student Sliced Inverse Regression. - Alessandro Chiancone; Florence Forbes; Stéphane Girard (Comput. Stat. Data Anal., 2017)

Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels. - Maïlys Lopes; Mathieu Fauvel; Stéphane Girard; David Sheeren (Remote. Sens., 2017)

Spectro-Temporal Heterogeneity Measures from Dense High Spatial Resolution Satellite Image Time Series: Application to Grassland Species Diversity Estimation. - Maïlys Lopes; Mathieu Fauvel; Annie Ouin; Stéphane Girard (Remote. Sens., 2017)

Extreme-value-theoretic estimation of local intrinsic dimensionality. - Laurent Amsaleg; Oussama Chelly; Teddy Furon; Stéphane Girard; Michael E. Houle; Ken-ichi Kawarabayashi; Michael Nett (Data Min. Knowl. Discov., 2018)

Dependence properties and Bayesian inference for asymmetric multivariate copulas. - Julyan Arbel; Marta Crispino; Stéphane Girard (J. Multivar. Anal., 2019)

Bayesian neural network unit priors and generalized Weibull-tail property. - Mariia Vladimirova; Julyan Arbel; Stéphane Girard (ACML, 2021)

A generative model for fBm with deep ReLU neural networks. - Michaël Allouche; Stéphane Girard; Emmanuel Gobet (J. Complex., 2022)

EV-GAN: Simulation of extreme events with ReLU neural networks. - Michaël Allouche; Stéphane Girard; Emmanuel Gobet (J. Mach. Learn. Res., 2022)

Advanced topics in Sliced Inverse Regression. - Stéphane Girard; Hadrien Lorenzo; Jérôme Saracco (J. Multivar. Anal., 2022)

Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image time-series. - Alexandre Constantin; Mathieu Fauvel; Stéphane Girard (Stat. Comput., 2022)

On automatic bias reduction for extreme expectile estimation. - Stéphane Girard; Gilles Stupfler; Antoine Usseglio-Carleve (Stat. Comput., 2022)

Joint Supervised Classification and Reconstruction of Irregularly Sampled Satellite Image Times Series. - Alexandre Constantin; Mathieu Fauvel; Stéphane Girard (IEEE Trans. Geosci. Remote. Sens., 2022)

Extreme partial least-squares. - Meryem Bousebata; Geoffroy Enjolras; Stéphane Girard (J. Multivar. Anal., 2023)

Reparameterization of extreme value framework for improved Bayesian workflow. - Théo Moins; Julyan Arbel; Stéphane Girard; Anne Dutfoy (Comput. Stat. Data Anal., 2023)

Estimation of extreme quantiles from heavy-tailed distributions with neural networks. - Michaël Allouche; Stéphane Girard; Emmanuel Gobet (Stat. Comput., 2024)

Shrinkage for extreme partial least-squares. - Julyan Arbel; Stéphane Girard; Hadrien Lorenzo (Stat. Comput., 2024)

Learning extreme expected shortfall and conditional tail moments with neural networks. Application to cryptocurrency data. - Michaël Allouche; Stéphane Girard; Emmanuel Gobet (Neural Networks, 2025)