Julie Josse
16 papers · 2016–2025 · 4 venues · across top CS/AI venues
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(4)
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(3)
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causal inference
(3)
missing value
(3)
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(2)
matrix completion
(2)
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(2)
doubly robust estimator
(2)
prediction interval
(2)
missing data
(2)
conformal prediction
(2)
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feature selection
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covariate shift
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quantile regression
(1)
time series forecasting
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joint learning
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(1)
policy learning
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supervised learning
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linear regression
(1)
Papers
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
AISTATS 2025
Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
JMLR 2025
Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis
AISTATS 2025
Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies
ICML 2025
MMD-based Variable Importance for Distributional Random Forest
AISTATS 2024
Positivity-free Policy Learning with Observational Data
AISTATS 2024
Conformal Prediction with Missing Values
ICML 2023
Adaptive Conformal Predictions for Time Series
ICML 2022
Whatβs a good imputation to predict with missing values?
NeurIPS 2021
Debiasing Averaged Stochastic Gradient Descent to handle missing values
NeurIPS 2020
Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data
NeurIPS 2020
Linear predictor on linearly-generated data with missing values: non consistency and solutions
AISTATS 2020
Missing Data Imputation using Optimal Transport
ICML 2020
NeuMiss networks: differentiable programming for supervised learning with missing values.
NeurIPS 2020
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
NeurIPS 2018
Bootstrap-Based Regularization for Low-Rank Matrix Estimation
JMLR 2016