HYR2PICS: Hybrid regularized reconstruction for combined parallel imaging and compressive sensing in MRI. - Claire Boyer; Philippe Ciuciu; Pierre Weiss; Sébastien Mériaux (ISBI, 2012)

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)

Adapting to unknown noise level in sparse deconvolution. - Claire Boyer; Yohann de Castro; Joseph Salmon (CoRR, 2016)

On the Generation of Sampling Schemes for Magnetic Resonance Imaging. - Claire Boyer; Nicolas Chauffert; Philippe Ciuciu; Jonas Kahn; Pierre Weiss (SIAM J. Imaging Sci., 2016)

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

On oracle-type local recovery guarantees in compressed sensing. - Ben Adcock; Claire Boyer; Simone Brugiapaglia (CoRR, 2018)

Accelerated proximal boosting. - Erwan Fouillen; Claire Boyer; Maxime Sangnier (CoRR, 2018)

Convex Regularization and Representer Theorems. - Claire Boyer; Antonin Chambolle; Yohann de Castro; Vincent Duval; Frédéric de Gournay; Pierre Weiss (CoRR, 2018)

Imputation and low-rank estimation with Missing Non At Random data. - Aude Sportisse; Claire Boyer; Julie Josse (CoRR, 2018)

On Representer Theorems and Convex Regularization. - Claire Boyer; Antonin Chambolle; Yohann de Castro; Vincent Duval; Frédéric de Gournay; Pierre Weiss (SIAM J. Optim., 2019)

Missing Data Imputation using Optimal Transport. - Boris Muzellec; Julie Josse; Claire Boyer; Marco Cuturi (ICML, 2020)

Debiasing Averaged Stochastic Gradient Descent to handle missing values. - Aude Sportisse; Claire Boyer; Aymeric Dieuleveut; Julie Josse (NeurIPS, 2020)

Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data. - Aude Sportisse; Claire Boyer; Julie Josse (NeurIPS, 2020)

Imputation and low-rank estimation with Missing Not At Random data. - Aude Sportisse; Claire Boyer; Julie Josse (Stat. Comput., 2020)

Analyzing the tree-layer structure of Deep Forests. - Ludovic Arnould; Claire Boyer; Erwan Scornet (ICML, 2021)

Near-optimal rate of consistency for linear models with missing values. - Alexis Ayme; Claire Boyer; Aymeric Dieuleveut; Erwan Scornet (ICML, 2022)

Minimax rate of consistency for linear models with missing values. - Alexis Ayme; Claire Boyer; Aymeric Dieuleveut; Erwan Scornet (CoRR, 2022)

Is interpolation benign for random forest regression? - Ludovic Arnould; Claire Boyer; Erwan Scornet (AISTATS, 2023)

Sparse tree-based Initialization for Neural Networks. - Patrick Lutz; Ludovic Arnould; Claire Boyer; Erwan Scornet (ICLR, 2023)

Naive imputation implicitly regularizes high-dimensional linear models. - Alexis Ayme; Claire Boyer; Aymeric Dieuleveut; Erwan Scornet (ICML, 2023)

Proximal boosting: Aggregating weak learners to minimize non-differentiable losses. - Erwan Fouillen; Claire Boyer; Maxime Sangnier (Neurocomputing, 2023)

On the asymptotic rate of convergence of Stochastic Newton algorithms and their Weighted Averaged versions. - Claire Boyer; Antoine Godichon-Baggioni (Comput. Optim. Appl., 2023)

Sampling Rates for ℓ 1-Synthesis. - Maximilian März; Claire Boyer; Jonas Kahn; Pierre Weiss (Found. Comput. Math., 2023)

Physics-informed machine learning as a kernel method. - Nathan Doumèche; Francis R. Bach; Gérard Biau; Claire Boyer (COLT, 2024)

Random features models: a way to study the success of naive imputation. - Alexis Ayme; Claire Boyer; Aymeric Dieuleveut; Erwan Scornet (ICML, 2024)

Physics-informed kernel learning. - Nathan Doumèche; Francis R. Bach; Gérard Biau; Claire Boyer (CoRR, 2024)

Correction: On the asymptotic rate of convergence of Stochastic Newton algorithms and their Weighted Averaged versions. - Claire Boyer; Antoine Godichon-Baggioni (Comput. Optim. Appl., 2024)

Model-based clustering with missing not at random data. - Aude Sportisse; Matthieu Marbac; Fabien Laporte; Gilles Celeux; Claire Boyer; Julie Josse; Christophe Biernacki (Stat. Comput., 2024)

A primer on linear classification with missing data. - Angel David Reyero Lobo; Alexis Ayme; Claire Boyer; Erwan Scornet (AISTATS, 2025)

Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization. - Yu-Han Wu; Pierre Marion; Gérard Biau; Claire Boyer (COLT, 2025)

Attention layers provably solve single-location regression. - Pierre Marion; Raphaël Berthier; Gérard Biau; Claire Boyer (ICLR, 2025)

An analysis of the noise schedule for score-based generative models. - Stanislas Strasman; Antonio Ocello; Claire Boyer; Sylvain Le Corff; Vincent Lemaire 002 (Trans. Mach. Learn. Res., 2025)

Optimal Transport-based Conformal Prediction. - Gauthier Thurin; Kimia Nadjahi; Claire Boyer (CoRR, 2025)

Forecasting time series with constraints. - Nathan Doumèche; Francis R. Bach; Éloi Bedek; Gérard Biau; Claire Boyer; Yannig Goude (CoRR, 2025)

Attention-based clustering. - Rodrigo Maulen-Soto; Claire Boyer; Pierre Marion (CoRR, 2025)