Saved in:
| Main Authors: | Abécassis, Judith, Zenati, Houssam, Boumaïza, Sami, Josse, Julie, Thirion, Bertrand |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.07323 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
by: Zenati, Houssam, et al.
Published: (2025)
by: Zenati, Houssam, et al.
Published: (2025)
Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis
by: Even, Mathieu, et al.
Published: (2025)
by: Even, Mathieu, et al.
Published: (2025)
Comparison of methods for mediation analysis with multiple correlated mediators
by: Appah, Mary, et al.
Published: (2024)
by: Appah, Mary, et al.
Published: (2024)
Classification problem in liability insurance using machine learning models: a comparative study
by: Qazvini, Marjan
Published: (2024)
by: Qazvini, Marjan
Published: (2024)
Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
by: Zenati, Houssam, et al.
Published: (2026)
by: Zenati, Houssam, et al.
Published: (2026)
Adapting tree-based multiple imputation methods for multi-level data? A simulation study
by: Föge, Nico, et al.
Published: (2024)
by: Föge, Nico, et al.
Published: (2024)
A comparative analysis of machine learning algorithms for predicting probabilities of default
by: Cristescu, Adrian Iulian, et al.
Published: (2025)
by: Cristescu, Adrian Iulian, et al.
Published: (2025)
Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation
by: Khellaf, Rémi, et al.
Published: (2025)
by: Khellaf, Rémi, et al.
Published: (2025)
Cluster Size Matters: A Comparative Study of Notip and pARI for Post Hoc Inference in fMRI
by: Peyrouset, Nils, et al.
Published: (2025)
by: Peyrouset, Nils, et al.
Published: (2025)
Changepoint Detection As Model Selection: A General Framework
by: Grantham, Michael, et al.
Published: (2026)
by: Grantham, Michael, et al.
Published: (2026)
Causal indirect effect of an HIV curative treatment: mediators subject to an assay limit and measurement error
by: Herath, Vindyani, et al.
Published: (2025)
by: Herath, Vindyani, et al.
Published: (2025)
Efficient Causal Discovery for Autoregressive Time Series
by: Fesanghary, Mohammad, et al.
Published: (2025)
by: Fesanghary, Mohammad, et al.
Published: (2025)
Adaptive Online Experimental Design for Causal Discovery
by: Elahi, Muhammad Qasim, et al.
Published: (2024)
by: Elahi, Muhammad Qasim, et al.
Published: (2024)
Causal machine learning for predicting treatment outcomes
by: Feuerriegel, Stefan, et al.
Published: (2024)
by: Feuerriegel, Stefan, et al.
Published: (2024)
Causal Responder Detection
by: Frostig, Tzviel, et al.
Published: (2024)
by: Frostig, Tzviel, et al.
Published: (2024)
Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
by: S, Saranya Ganesh, et al.
Published: (2025)
by: S, Saranya Ganesh, et al.
Published: (2025)
Density Ratio-Free Doubly Robust Proxy Causal Learning
by: Bozkurt, Bariscan, et al.
Published: (2025)
by: Bozkurt, Bariscan, et al.
Published: (2025)
Efficient Causal Structure Learning via Modular Subgraph Integration
by: Sun, Haixiang, et al.
Published: (2026)
by: Sun, Haixiang, et al.
Published: (2026)
The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information
by: Abler, D., et al.
Published: (2025)
by: Abler, D., et al.
Published: (2025)
Testing Generalizability in Causal Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)
by: Manela, Daniel de Vassimon, et al.
Published: (2024)
Time-Varying Home Field Advantage in Football: Learning from a Non-Stationary Causal Process
by: Qi, Minhao, et al.
Published: (2025)
by: Qi, Minhao, et al.
Published: (2025)
Explainable Federated Bayesian Causal Inference and Its Application in Advanced Manufacturing
by: Xiao, Xiaofeng, et al.
Published: (2025)
by: Xiao, Xiaofeng, et al.
Published: (2025)
Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments
by: Kovačević, Luka, et al.
Published: (2024)
by: Kovačević, Luka, et al.
Published: (2024)
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting
by: Das, Keshav, et al.
Published: (2025)
by: Das, Keshav, et al.
Published: (2025)
Causal Feature Learning in the Social Sciences
by: Huang, Jingzhou, et al.
Published: (2025)
by: Huang, Jingzhou, et al.
Published: (2025)
Curious Causality-Seeking Agents Learn Meta Causal World
by: Zhao, Zhiyu, et al.
Published: (2025)
by: Zhao, Zhiyu, et al.
Published: (2025)
Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
by: Zenati, Houssam, et al.
Published: (2025)
by: Zenati, Houssam, et al.
Published: (2025)
SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling
by: Vowels, Matthew J.
Published: (2023)
by: Vowels, Matthew J.
Published: (2023)
Advancing Causal Inference: A Nonparametric Approach to ATE and CATE Estimation with Continuous Treatments
by: Souto, Hugo Gobato, et al.
Published: (2024)
by: Souto, Hugo Gobato, et al.
Published: (2024)
Valuing an Engagement Surface using a Large Scale Dynamic Causal Model
by: Mukerji, Abhimanyu, et al.
Published: (2024)
by: Mukerji, Abhimanyu, et al.
Published: (2024)
Causal Inference with Double/Debiased Machine Learning for Evaluating the Health Effects of Multiple Mismeasured Pollutants
by: Xu, Gang, et al.
Published: (2024)
by: Xu, Gang, et al.
Published: (2024)
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes
by: Du, Jin-Hong, et al.
Published: (2024)
by: Du, Jin-Hong, et al.
Published: (2024)
Kernel Treatment Effects with Adaptively Collected Data
by: Zenati, Houssam, et al.
Published: (2025)
by: Zenati, Houssam, et al.
Published: (2025)
An unsupervised learning approach to evaluate questionnaire data -- what one can learn from violations of measurement invariance
by: Hahn-Klimroth, Max, et al.
Published: (2023)
by: Hahn-Klimroth, Max, et al.
Published: (2023)
Deep learning-based pavement performance modeling using multiple distress indicators and road work history
by: Gao, Lu, et al.
Published: (2026)
by: Gao, Lu, et al.
Published: (2026)
Causal Fairness for Survival Analysis
by: Plecko, Drago
Published: (2026)
by: Plecko, Drago
Published: (2026)
Causal Judge Evaluation: Calibrated Surrogate Metrics for LLM Systems
by: Landesberg, Eddie, et al.
Published: (2025)
by: Landesberg, Eddie, et al.
Published: (2025)
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
by: Zhou, Zihan, et al.
Published: (2024)
by: Zhou, Zihan, et al.
Published: (2024)
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
by: Chakraborty, Atlanta, et al.
Published: (2025)
by: Chakraborty, Atlanta, et al.
Published: (2025)
From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies
by: Gutman, Rom, et al.
Published: (2025)
by: Gutman, Rom, et al.
Published: (2025)
Similar Items
-
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
by: Zenati, Houssam, et al.
Published: (2025) -
Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis
by: Even, Mathieu, et al.
Published: (2025) -
Comparison of methods for mediation analysis with multiple correlated mediators
by: Appah, Mary, et al.
Published: (2024) -
Classification problem in liability insurance using machine learning models: a comparative study
by: Qazvini, Marjan
Published: (2024) -
Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
by: Zenati, Houssam, et al.
Published: (2026)