Supervised Quantile Normalisation. - Marine Le Morvan; Jean-Philippe Vert (CoRR, 2017)

NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis. - Marine Le Morvan; Andrei Yu. Zinovyev; Jean-Philippe Vert (PLoS Comput. Biol., 2017)

WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models. - Marine Le Morvan; Jean-Philippe Vert (ICML, 2018)

Learning from genomic data: efficient representations and algorithms. (Développement de représentations et d'algorithmes efficaces pour l'apprentissage statistique sur des données génomiques). - Marine Le Morvan (2018)

Linear predictor on linearly-generated data with missing values: non consistency and solutions. - Marine Le Morvan; Nicolas Prost; Julie Josse; Erwan Scornet; Gaël Varoquaux (AISTATS, 2020)

NeuMiss networks: differentiable programming for supervised learning with missing values. - Marine Le Morvan; Julie Josse; Thomas Moreau 001; Erwan Scornet; Gaël Varoquaux (NeurIPS, 2020)

Neumann networks: differential programming for supervised learning with missing values. - Marine Le Morvan; Julie Josse; Thomas Moreau 001; Erwan Scornet; Gaël Varoquaux (CoRR, 2020)

What's a good imputation to predict with missing values? - Marine Le Morvan; Julie Josse; Erwan Scornet; Gaël Varoquaux (NeurIPS, 2021)

Benchmarking missing-values approaches for predictive models on health databases. - Alexandre Perez-Lebel; Gaël Varoquaux; Marine Le Morvan; Julie Josse; Jean-Baptiste Poline (CoRR, 2022)

Beyond calibration: estimating the grouping loss of modern neural networks. - Alexandre Perez-Lebel; Marine Le Morvan; Gaël Varoquaux (ICLR, 2023)

Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration. - Alexandre Perez-Lebel; Gaël Varoquaux; Sanmi Koyejo; Matthieu Doutreligne; Marine Le Morvan (AISTATS, 2025)

Imputation for prediction: beware of diminishing returns. - Marine Le Morvan; Gaël Varoquaux (ICLR, 2025)

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data. - Jingang Qu; David Holzmüller; Gaël Varoquaux; Marine Le Morvan (CoRR, 2025)