Cover Image

Predictive Uncertainty Quantification with Missing Covariates

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zaffran, Margaux, Josse, Julie, Romano, Yaniv, Dieuleveut, Aymeric
Format:	Preprint
Published:	2024
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncertainty Quantification of MLE for Entity Ranking with Covariates
by: Fan, Jianqing, et al.
Published: (2022)

Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis
by: Even, Mathieu, et al.
Published: (2025)

Valid Selection among Conformal Sets
by: Hegazy, Mahmoud, et al.
Published: (2025)

Quantifying Treatment Effects: Estimating Risk Ratios in Causal Inference
by: Boughdiri, Ahmed, et al.
Published: (2024)

Prediction-Centric Uncertainty Quantification via MMD
by: Shen, Zheyang, et al.
Published: (2024)

MMD-based Variable Importance for Distributional Random Forest
by: Bénard, Clément, et al.
Published: (2023)

Optimal Treatment Rules under Missing Predictive Covariates: A Covariate-Balancing Doubly Robust Approach
by: Zhang, Yue, et al.
Published: (2025)

A Unified Framework for the Transportability of Population-Level Causal Measures
by: Boughdiri, Ahmed, et al.
Published: (2025)

Risk ratio, odds ratio, risk difference... Which causal measure is easier to generalize?
by: Colnet, Bénédicte, et al.
Published: (2023)

Reweighting the RCT for generalization: finite sample error and variable selection
by: Colnet, Bénédicte, et al.
Published: (2022)

Robust Conformal Outlier Detection under Contaminated Reference Data
by: Bashari, Meshi, et al.
Published: (2025)

Accounting for Missing Covariates in Heterogeneous Treatment Estimation
by: Yamin, Khurram, et al.
Published: (2024)

Uncertainty Quantification in Bayesian Clustering
by: Page, Garritt L., et al.
Published: (2025)

Treatment Effect Estimation in Causal Survival Analysis: Practical Recommendations
by: Voinot, Charlotte, et al.
Published: (2025)

R-miss-tastic: a unified platform for missing values methods and workflows
by: Mayer, Imke, et al.
Published: (2019)

Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation
by: Khellaf, Rémi, et al.
Published: (2025)

Nonparametric Estimation of Path-specific Effects in Presence of Nonignorable Missing Covariates
by: Shan, Jiawei, et al.
Published: (2024)

Establishing the Parallels and Differences Between Right-Censored and Missing Covariates
by: Vazquez, Jesus E., et al.
Published: (2024)

Policy learning under constraint: Maximizing a primary outcome while controlling an adverse event
by: Fuentes-Vicente, Laura, et al.
Published: (2026)

Synthetic-Powered Multiple Testing with FDR Control
by: Lee, Yonghoon, et al.
Published: (2026)

Bayesian Covariance Uncertainty for Adaptive Pilot-Sampling Termination in Multi-fidelity Uncertainty Quantification
by: Coons, Thomas E., et al.
Published: (2025)

Efficient Input Uncertainty Quantification for Ratio Estimator
by: He, Linyun, et al.
Published: (2024)

Model Uncertainty and Missing Data: An Objective Bayesian Perspective
by: García-Donato, Gonzalo, et al.
Published: (2024)

Uncertainty Quantification With Multiple Sources
by: Ying, Mufang, et al.
Published: (2024)

Large Scale Partial Correlation Screening with Uncertainty Quantification
by: Neo, Emily, et al.
Published: (2025)

Self-Supervised Conformal Prediction with Equivariant Bootstrapping for Image Uncertainty Quantification
by: Aldridge, Henry J., et al.
Published: (2026)

Optimal Forecast Reconciliation with Uncertainty Quantification
by: Møller, Jan Kloppenborg, et al.
Published: (2024)

Interventional Processes for Causal Uncertainty Quantification
by: Dance, Hugh, et al.
Published: (2024)

Doubly Robust Machine Learning for Population Size Estimation with Missing Covariates: Application to Gaza Conflict Mortality
by: Rubio, Mateo Dulce, et al.
Published: (2026)

Uncertainty Quantification for Ranking with Heterogeneous Preferences
by: Fan, Jianqing, et al.
Published: (2025)

Conditional Predictive Inference for Missing Outcomes
by: Lee, Yonghoon, et al.
Published: (2024)

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
by: Lugosi, Gábor, et al.
Published: (2025)

PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
by: Agarwal, Abhineet, et al.
Published: (2025)

Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment
by: Heng, Siyu, et al.
Published: (2023)

Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data
by: Suen, Man Ho, et al.
Published: (2025)

Uncertainty Quantification in Bayesian Reduced-Rank Sparse Regressions
by: Pintado, Maria F., et al.
Published: (2023)

Fair Conformal Prediction for Incomplete Covariate Data
by: Kong, Jingsen, et al.
Published: (2025)

Hierarchical Bayesian Modeling for Uncertainty Quantification and Reliability Updating using Data
by: Jia, Xinyu, et al.
Published: (2024)

Bend to Mend: Toward Trustworthy Variational Bayes with Valid Uncertainty Quantification
by: Liu, Jiaming, et al.
Published: (2025)

Likelihood-free Posterior Density Learning for Uncertainty Quantification in Inference Problems
by: Zhang, Rui, et al.
Published: (2025)