Recalage de signaux et analyse de variance fonctionnelle par ondelettes. Applications au domaine biomédical. (Landmark-based registration and functional analysis of variance with wavelets). - Jérémie Bigot (2003)

Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping. - Jérémie Bigot; Sébastien Gadat; Jean-Michel Loubes (J. Math. Imaging Vis., 2009)

Estimation of Translation, Rotation, and Scaling between Noisy Images Using the Fourier–Mellin Transform. - Jérémie Bigot; Fabrice Gamboa; Myriam Vimond (SIAM J. Imaging Sci., 2009)

Smoothing under Diffeomorphic Constraints with Homeomorphic Splines. - Jérémie Bigot; Sébastien Gadat (SIAM J. Numer. Anal., 2010)

Group Lasso Estimation of High-dimensional Covariance Matrices. - Jérémie Bigot; Rolando J. Biscay; Jean-Michel Loubes; Lilian Muñiz-Alvarez (J. Mach. Learn. Res., 2011)

A new statistical test based on the wavelet cross-spectrum to detect time-frequency dependence between non-stationary signals: Application to the analysis of cortico-muscular interactions. - Jérémie Bigot; Marieke Longcamp; Fabien Dal Maso; David Amarantini (NeuroImage, 2011)

Random Action of Compact Lie Groups and Minimax Estimation of a Mean Pattern. - Jérémie Bigot; Claire Christophe; Sébastien Gadat (IEEE Trans. Inf. Theory, 2012)

Geometric PCA of Images. - Jérémie Bigot; Raúl Gouet; Alfredo López (SIAM J. Imaging Sci., 2013)

An Algorithm for Variable Density Sampling with Block-Constrained Acquisition. - Claire Boyer; Pierre Weiss; Jérémie Bigot (SIAM J. Imaging Sci., 2014)

Compressed sensing with structured sparsity and structured acquisition. - Claire Boyer; Jérémie Bigot; Pierre Weiss (CoRR, 2015)

Estimation of linear operators from scattered impulse responses. - Jérémie Bigot; Paul Escande; Pierre Weiss (CoRR, 2016)

An Analysis of Block Sampling Strategies in Compressed Sensing. - Jérémie Bigot; Claire Boyer; Pierre Weiss (IEEE Trans. Inf. Theory, 2016)

Regularized Barycenters in the Wasserstein Space. - Elsa Cazelles; Jérémie Bigot; Nicolas Papadakis (GSI, 2017)

Generalized SURE for optimal shrinkage of singular values in low-rank matrix denoising. - Jérémie Bigot; Charles Deledalle; Delphine Féral (J. Mach. Learn. Res., 2017)

Data-Oriented Algorithm for Real-Time Estimation of Flow Rates and Flow Directions in a Water Distribution Network. - Christophe Dumora; David Auber; Jérémie Bigot; Vincent Couallier; Cyril Leclerc (CoRR, 2018)

Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space. - Elsa Cazelles; Vivien Seguy; Jérémie Bigot; Marco Cuturi; Nicolas Papadakis (SIAM J. Sci. Comput., 2018)

Toeplitz Hermitian Positive Definite Matrix Machine Learning Based on Fisher Metric. - Yann Cabanes; Frédéric Barbaresco; Marc Arnaudon; Jérémie Bigot (GSI, 2019)

Penalization of Barycenters in the Wasserstein Space. - Jérémie Bigot; Elsa Cazelles; Nicolas Papadakis (SIAM J. Math. Anal., 2019)

Sensor selection on graphs via data-driven node sub-sampling in network time series. - Yiye Jiang; Jérémie Bigot; Sofian Maabout (CoRR, 2020)

Low-rank matrix denoising for count data using unbiased Kullback-Leibler risk estimation. - Jérémie Bigot; Charles Deledalle (Comput. Stat. Data Anal., 2022)

Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia. - Erell Gachon; Jérémie Bigot; Elsa Cazelles; Aguirre Mimoun; Jean-Philippe Vial (CoRR, 2024)

Online graph topology learning from matrix-valued time series. - Yiye Jiang; Jérémie Bigot; Sofian Maabout (Comput. Stat. Data Anal., 2025)

Scalable and consistent embedding of probability measures into Hilbert spaces via measure quantization. - Erell Gachon; Elsa Cazelles; Jérémie Bigot (CoRR, 2025)

High-dimensional ridge regression with random features for non-identically distributed data with a variance profile. - Issa-Mbenard Dabo; Jérémie Bigot (CoRR, 2025)