Counterfactual Survival Q-learning via Buckley-James Boosting, with Applications to ACTG 175 and CALGB 8923
Fuente:
arXiv
Guardado en:
| Autores principales: | Lee, Jeongjin, Kim, Jong-Min |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Counterfactual Q Learning via the Linear Buckley James Method for Longitudinal Survival Data
por: Lee, Jeongjin, et al.
Publicado: (2025)
por: Lee, Jeongjin, et al.
Publicado: (2025)
Semiparametric Counterfactual Regression
por: Kim, Kwangho
Publicado: (2025)
por: Kim, Kwangho
Publicado: (2025)
Estimating Heterogeneous Treatment Effects on Survival Outcomes Using Counterfactual Censoring Unbiased Transformations
por: Xu, Shenbo, et al.
Publicado: (2024)
por: Xu, Shenbo, et al.
Publicado: (2024)
Transfer Q-learning
por: Chen, Elynn, et al.
Publicado: (2022)
por: Chen, Elynn, et al.
Publicado: (2022)
Geometry Adaptive Counterfactual Distribution Learning with Diffusion-Guided Smoothing
por: Kim, Kwangho
Publicado: (2026)
por: Kim, Kwangho
Publicado: (2026)
RieszBoost: Gradient Boosting for Riesz Regression
por: Lee, Kaitlyn J., et al.
Publicado: (2025)
por: Lee, Kaitlyn J., et al.
Publicado: (2025)
DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations
por: Zhu, Jiageng, et al.
Publicado: (2024)
por: Zhu, Jiageng, et al.
Publicado: (2024)
Hypothesis testing for partial tail correlation in multivariate extremes
por: Kim, Mihyun, et al.
Publicado: (2022)
por: Kim, Mihyun, et al.
Publicado: (2022)
Group Shapley Value and Counterfactual Simulations in a Structural Model
por: Kwon, Yongchan, et al.
Publicado: (2024)
por: Kwon, Yongchan, et al.
Publicado: (2024)
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks
por: Liu, Xin, et al.
Publicado: (2024)
por: Liu, Xin, et al.
Publicado: (2024)
Geometric criteria for identifying extremal dependence and flexible modeling via additive mixtures
por: Lee, Jeongjin, et al.
Publicado: (2025)
por: Lee, Jeongjin, et al.
Publicado: (2025)
DoubleGen: Debiased Generative Modeling of Counterfactuals
por: Luedtke, Alex, et al.
Publicado: (2025)
por: Luedtke, Alex, et al.
Publicado: (2025)
Counterfactual Generative Models for Time-Varying Treatments
por: Wu, Shenghao, et al.
Publicado: (2023)
por: Wu, Shenghao, et al.
Publicado: (2023)
Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
por: Sun, Jianle, et al.
Publicado: (2026)
por: Sun, Jianle, et al.
Publicado: (2026)
Causal and Counterfactual Views of Missing Data Models
por: Nabi, Razieh, et al.
Publicado: (2022)
por: Nabi, Razieh, et al.
Publicado: (2022)
Advancing Counterfactual Inference through Nonlinear Quantile Regression
por: Xie, Shaoan, et al.
Publicado: (2023)
por: Xie, Shaoan, et al.
Publicado: (2023)
Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
por: Wei, Song, et al.
Publicado: (2023)
por: Wei, Song, et al.
Publicado: (2023)
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
por: Wu, Anpeng, et al.
Publicado: (2024)
por: Wu, Anpeng, et al.
Publicado: (2024)
Causal Contrastive Learning for Counterfactual Regression Over Time
por: Bouchattaoui, Mouad El, et al.
Publicado: (2024)
por: Bouchattaoui, Mouad El, et al.
Publicado: (2024)
Counterfactual Cocycles: A Framework for Robust and Coherent Counterfactual Transports
por: Dance, Hugh, et al.
Publicado: (2024)
por: Dance, Hugh, et al.
Publicado: (2024)
Response to Discussions of "Causal and Counterfactual Views of Missing Data Models"
por: Nabi, Razieh, et al.
Publicado: (2025)
por: Nabi, Razieh, et al.
Publicado: (2025)
Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data
por: Yin, Xiaohui, et al.
Publicado: (2026)
por: Yin, Xiaohui, et al.
Publicado: (2026)
Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics
por: Ehyaei, Ahmad-Reza, et al.
Publicado: (2024)
por: Ehyaei, Ahmad-Reza, et al.
Publicado: (2024)
Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries
por: Chao, Patrick, et al.
Publicado: (2023)
por: Chao, Patrick, et al.
Publicado: (2023)
Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness
por: Machado, Agathe Fernandes, et al.
Publicado: (2024)
por: Machado, Agathe Fernandes, et al.
Publicado: (2024)
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
por: Zhou, Zeyu, et al.
Publicado: (2023)
por: Zhou, Zeyu, et al.
Publicado: (2023)
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
por: Wang, Jitao, et al.
Publicado: (2025)
por: Wang, Jitao, et al.
Publicado: (2025)
CFLight: Enhancing Safety with Traffic Signal Control through Counterfactual Learning
por: Li, Mingyuan, et al.
Publicado: (2025)
por: Li, Mingyuan, et al.
Publicado: (2025)
Watermarking Counterfactual Explanations
por: Guo, Hangzhi, et al.
Publicado: (2024)
por: Guo, Hangzhi, et al.
Publicado: (2024)
Interpretable Machine Learning for Survival Analysis
por: Langbein, Sophie Hanna, et al.
Publicado: (2024)
por: Langbein, Sophie Hanna, et al.
Publicado: (2024)
Fréchet Geodesic Boosting
por: Zhou, Yidong, et al.
Publicado: (2025)
por: Zhou, Yidong, et al.
Publicado: (2025)
Optimal Transport on Categorical Data for Counterfactuals using Compositional Data and Dirichlet Transport
por: Machado, Agathe Fernandes, et al.
Publicado: (2025)
por: Machado, Agathe Fernandes, et al.
Publicado: (2025)
No $D_{\text{train}}$: Model-Agnostic Counterfactual Explanations Using Reinforcement Learning
por: Sun, Xiangyu, et al.
Publicado: (2024)
por: Sun, Xiangyu, et al.
Publicado: (2024)
Nonparametric Regression Discontinuity Designs with Survival Outcomes
por: Schuessler, Maximilian, et al.
Publicado: (2026)
por: Schuessler, Maximilian, et al.
Publicado: (2026)
DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
por: Wu, Dongze, et al.
Publicado: (2025)
por: Wu, Dongze, et al.
Publicado: (2025)
Counterfactual identifiability beyond global monotonicity: non-monotone triangular structural causal models
por: Tan, Pengcheng, et al.
Publicado: (2026)
por: Tan, Pengcheng, et al.
Publicado: (2026)
Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information
por: Oganisian, Arman, et al.
Publicado: (2024)
por: Oganisian, Arman, et al.
Publicado: (2024)
Deep Q-Exponential Processes
por: Chang, Zhi, et al.
Publicado: (2024)
por: Chang, Zhi, et al.
Publicado: (2024)
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
por: Komanduri, Aneesh, et al.
Publicado: (2024)
por: Komanduri, Aneesh, et al.
Publicado: (2024)
Stagewise Boosting Distributional Regression
por: Wetscher, Mattias, et al.
Publicado: (2024)
por: Wetscher, Mattias, et al.
Publicado: (2024)
Ejemplares similares
-
Counterfactual Q Learning via the Linear Buckley James Method for Longitudinal Survival Data
por: Lee, Jeongjin, et al.
Publicado: (2025) -
Semiparametric Counterfactual Regression
por: Kim, Kwangho
Publicado: (2025) -
Estimating Heterogeneous Treatment Effects on Survival Outcomes Using Counterfactual Censoring Unbiased Transformations
por: Xu, Shenbo, et al.
Publicado: (2024) -
Transfer Q-learning
por: Chen, Elynn, et al.
Publicado: (2022) -
Geometry Adaptive Counterfactual Distribution Learning with Diffusion-Guided Smoothing
por: Kim, Kwangho
Publicado: (2026)