Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
Fuente:
arXiv
Saved in:
| Main Authors: | Meir, Tomer, Shalit, Uri, Gorfine, Malka |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Discrete-time Competing-Risks Regression with or without Penalization
by: Meir, Tomer, et al.
Published: (2023)
by: Meir, Tomer, et al.
Published: (2023)
PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks and Optional Penalization
by: Meir, Tomer, et al.
Published: (2022)
by: Meir, Tomer, et al.
Published: (2022)
Structured Hybrid Mechanistic Models for Robust Estimation of Time-Dependent Intervention Outcomes
by: Meir, Tomer, et al.
Published: (2026)
by: Meir, Tomer, et al.
Published: (2026)
Flexible Deep Neural Networks for Partially Linear Survival Data: Estimation and Survival Inference
by: Arie, Asaf Ben, et al.
Published: (2025)
by: Arie, Asaf Ben, et al.
Published: (2025)
Confidence Intervals and Simultaneous Confidence Bands Based on Deep Learning
by: Arie, Asaf Ben, et al.
Published: (2024)
by: Arie, Asaf Ben, et al.
Published: (2024)
Preference-based Conditional Treatment Effects and Policy Learning
by: Parnas, Dovid, et al.
Published: (2026)
by: Parnas, Dovid, et al.
Published: (2026)
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators
by: Linial, Ori, et al.
Published: (2024)
by: Linial, Ori, et al.
Published: (2024)
Estimating Heterogeneous Treatment Effects on Survival Outcomes Using Counterfactual Censoring Unbiased Transformations
by: Xu, Shenbo, et al.
Published: (2024)
by: Xu, Shenbo, et al.
Published: (2024)
Set Valued Predictions For Robust Domain Generalization
by: Tsibulsky, Ron, et al.
Published: (2025)
by: Tsibulsky, Ron, et al.
Published: (2025)
INSIGHTS: Demonstration-Based Summaries of Time Series Predictors
by: Porat, Bar Eini, et al.
Published: (2026)
by: Porat, Bar Eini, et al.
Published: (2026)
Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data
by: Frauen, Dennis, et al.
Published: (2025)
by: Frauen, Dennis, 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)
Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
by: Paul, Animesh Kumar, et al.
Published: (2025)
by: Paul, Animesh Kumar, et al.
Published: (2025)
On the ERM Principle in Meta-Learning
by: Alon, Yannay, et al.
Published: (2024)
by: Alon, Yannay, et al.
Published: (2024)
Malign Overfitting: Interpolation Can Provably Preclude Invariance
by: Wald, Yoav, et al.
Published: (2022)
by: Wald, Yoav, et al.
Published: (2022)
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data
by: Kim, Sehwan, et al.
Published: (2025)
by: Kim, Sehwan, et al.
Published: (2025)
Joint auto-encoders: a flexible multi-task learning framework
by: Epstein, Baruch, et al.
Published: (2017)
by: Epstein, Baruch, et al.
Published: (2017)
Aiming for Relevance
by: Porat, Bar Eini, et al.
Published: (2024)
by: Porat, Bar Eini, et al.
Published: (2024)
On Local Overfitting and Forgetting in Deep Neural Networks
by: Stern, Uri, et al.
Published: (2024)
by: Stern, Uri, et al.
Published: (2024)
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
A Semiparametric Bayesian Method for Instrumental Variable Analysis with Partly Interval-Censored Time-to-Event Outcome
by: Cui, Elvis Han, et al.
Published: (2025)
by: Cui, Elvis Han, et al.
Published: (2025)
Adaptive Experimentation for Censored Survival Outcomes
by: Wang, Yuxin, et al.
Published: (2026)
by: Wang, Yuxin, et al.
Published: (2026)
Mastering Rare Event Analysis: Optimal Subsample Size in Logistic and Cox Regressions
by: Agassi, Tal, et al.
Published: (2024)
by: Agassi, Tal, et al.
Published: (2024)
Learning Robust Treatment Rules for Censored Data
by: Cui, Yifan, et al.
Published: (2024)
by: Cui, Yifan, et al.
Published: (2024)
Heterogeneous Treatment Effects in Panel Data
by: Levi, Retsef, et al.
Published: (2024)
by: Levi, Retsef, et al.
Published: (2024)
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
by: Jolicoeur-Martineau, Alexia, et al.
Published: (2023)
by: Jolicoeur-Martineau, Alexia, et al.
Published: (2023)
TabImpute: Universal Zero-Shot Imputation for Tabular Data
by: Feitelberg, Jacob, et al.
Published: (2025)
by: Feitelberg, Jacob, et al.
Published: (2025)
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
Convergence and Sample Complexity of First-Order Methods for Agnostic Reinforcement Learning
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
CenTime: Event-Conditional Modelling of Censoring in Survival Analysis
by: Shahin, Ahmed H., et al.
Published: (2023)
by: Shahin, Ahmed H., et al.
Published: (2023)
Is merging worth it? Securely evaluating the information gain for causal dataset acquisition
by: Fawkes, Jake, et al.
Published: (2024)
by: Fawkes, Jake, et al.
Published: (2024)
ImputeGAP: A Comprehensive Library for Time Series Imputation
by: Nater, Quentin, et al.
Published: (2025)
by: Nater, Quentin, et al.
Published: (2025)
Unlocking Retrospective Prevalent Information in EHRs -- a Pairwise Pseudolikelihood Approach
by: Keret, Nir, et al.
Published: (2023)
by: Keret, Nir, et al.
Published: (2023)
Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions
by: Klein, Omer Noy, et al.
Published: (2025)
by: Klein, Omer Noy, et al.
Published: (2025)
The Hidden Cost of Approximation in Online Mirror Descent
by: Schlisselberg, Ofir, et al.
Published: (2025)
by: Schlisselberg, Ofir, et al.
Published: (2025)
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
by: Sherman, Uri, et al.
Published: (2023)
by: Sherman, Uri, et al.
Published: (2023)
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data
by: Li, Mengxuan, et al.
Published: (2025)
by: Li, Mengxuan, et al.
Published: (2025)
Data-Driven Estimation of Heterogeneous Treatment Effects
by: Tran, Christopher, et al.
Published: (2023)
by: Tran, Christopher, et al.
Published: (2023)
Set-Valued Policy Learning
by: Fuentes-Vicente, Laura, et al.
Published: (2026)
by: Fuentes-Vicente, Laura, et al.
Published: (2026)
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects
by: Yao, Dong, et al.
Published: (2024)
by: Yao, Dong, et al.
Published: (2024)
Similar Items
-
Discrete-time Competing-Risks Regression with or without Penalization
by: Meir, Tomer, et al.
Published: (2023) -
PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks and Optional Penalization
by: Meir, Tomer, et al.
Published: (2022) -
Structured Hybrid Mechanistic Models for Robust Estimation of Time-Dependent Intervention Outcomes
by: Meir, Tomer, et al.
Published: (2026) -
Flexible Deep Neural Networks for Partially Linear Survival Data: Estimation and Survival Inference
by: Arie, Asaf Ben, et al.
Published: (2025) -
Confidence Intervals and Simultaneous Confidence Bands Based on Deep Learning
by: Arie, Asaf Ben, et al.
Published: (2024)