Erwan Scornet

According to our database, Erwan Scornet authored at least 32 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

WoodTapper: a Python package for explaining decision tree ensembles.

Abdoulaye Sakho, Jad Aouad, Carl-Erik Gauthier, Emmanuel Malherbe, Erwan Scornet

J. Open Source Softw., May, 2026

Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data.

Ferdinand Genans, Erwan Scornet

CoRR, May, 2026

Principled Federated Random Forests for Heterogeneous Data.

Rémi Khellaf, Erwan Scornet, Aurélien Bellet, Julie Josse

CoRR, February, 2026

Privacy Amplification by Missing Data.

Simon Roburin, Rafaël Pinot, Erwan Scornet

CoRR, February, 2026

2025

When Pattern-by-Pattern Works: Theoretical and Empirical Insights for Logistic Models with Missing Values.

Christophe Muller, Erwan Scornet, Julie Josse

CoRR, July, 2025

Asymptotic Normality of Infinite Centered Random Forests -Application to Imbalanced Classification.

Moria Mayala, Erwan Scornet, Charles Tillier, Olivier Wintenberger

CoRR, June, 2025

Harnessing Mixed Features for Imbalance Data Oversampling: Application to Bank Customers Scoring.

Abdoulaye Sakho, Emmanuel Malherbe, Carl-Erik Gauthier, Erwan Scornet

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2025

A Unified Framework for the Transportability of Population-Level Causal Measures.

Ahmed Boughdiri, Clément Berenfeld, Julie Josse, Erwan Scornet

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies.

Ahmed Boughdiri, Julie Josse, Erwan Scornet

Proceedings of the Forty-second International Conference on Machine Learning, 2025

A primer on linear classification with missing data.

Angel David Reyero Lobo, Alexis Ayme, Claire Boyer, Erwan Scornet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Theoretical and experimental study of SMOTE: limitations and comparisons of rebalancing strategies.

Abdoulaye Sakho, Erwan Scornet, Emmanuel Malherbe

CoRR, 2024

Random features models: a way to study the success of naive imputation.

Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Naive imputation implicitly regularizes high-dimensional linear models.

Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

Proceedings of the International Conference on Machine Learning, 2023

Sparse tree-based Initialization for Neural Networks.

Patrick Lutz, Ludovic Arnould, Claire Boyer, Erwan Scornet

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Is interpolation benign for random forest regression?

Ludovic Arnould, Claire Boyer, Erwan Scornet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Minimax rate of consistency for linear models with missing values.

Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

CoRR, 2022

Near-optimal rate of consistency for linear models with missing values.

Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

Proceedings of the International Conference on Machine Learning, 2022

SHAFF: Fast and consistent SHApley eFfect estimates via random Forests.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA.

Clément Bénard, Sébastien Da Veiga, Erwan Scornet

CoRR, 2021

What's a good imputation to predict with missing values?

Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Analyzing the tree-layer structure of Deep Forests.

Ludovic Arnould, Claire Boyer, Erwan Scornet

Proceedings of the 38th International Conference on Machine Learning, 2021

Interpretable Random Forests via Rule Extraction.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Neumann networks: differential programming for supervised learning with missing values.

Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux

CoRR, 2020

NeuMiss networks: differentiable programming for supervised learning with missing values.

Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Linear predictor on linearly-generated data with missing values: non consistency and solutions.

Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

SIRUS: making random forests interpretable.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

CoRR, 2019

AMF: Aggregated Mondrian Forests for Online Learning.

Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet

CoRR, 2019

On the consistency of supervised learning with missing values.

Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux

CoRR, 2019

2017

Universal consistency and minimax rates for online Mondrian Forests.

Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Random Forests and Kernel Methods.

Erwan Scornet

IEEE Trans. Inf. Theory, 2016

On the asymptotics of random forests.

Erwan Scornet

J. Multivar. Anal., 2016

Neural Random Forests.

Gérard Biau, Erwan Scornet, Johannes Welbl

CoRR, 2016