Marginal and Conditional Importance Measures from Machine Learning Models and Their Relationship with Conditional Average Treatment Effect
Fuente:
arXiv
Guardado en:
| Autores principales: | Khan, Mohammad Kaviul Anam, Saarela, Olli, Kustra, Rafal |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
por: Shi, Pengfei, et al.
Publicado: (2024)
por: Shi, Pengfei, et al.
Publicado: (2024)
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
por: Melnychuk, Valentyn, et al.
Publicado: (2025)
por: Melnychuk, Valentyn, et al.
Publicado: (2025)
Conditional Average Treatment Effect Estimation Under Hidden Confounders
por: Aloui, Ahmed, et al.
Publicado: (2025)
por: Aloui, Ahmed, et al.
Publicado: (2025)
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
por: Nagai, Tomoko, et al.
Publicado: (2024)
por: Nagai, Tomoko, et al.
Publicado: (2024)
Learning Conditional Averages
por: Bressan, Marco, et al.
Publicado: (2026)
por: Bressan, Marco, et al.
Publicado: (2026)
Causal Clustering for Conditional Average Treatment Effects Estimation and Subgroup Discovery
por: Wang, Zilong, et al.
Publicado: (2025)
por: Wang, Zilong, et al.
Publicado: (2025)
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
por: Kato, Masahiro
Publicado: (2024)
por: Kato, Masahiro
Publicado: (2024)
A Bayesian Additive Regression Tree Model for Learning Conditional Average Treatment Effects in Regression Discontinuity Designs
por: Alcantara, Rafael, et al.
Publicado: (2025)
por: Alcantara, Rafael, et al.
Publicado: (2025)
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
por: Huang, Yiyan, et al.
Publicado: (2024)
por: Huang, Yiyan, et al.
Publicado: (2024)
Calibrated Inference for the Conditional Average Treatment Effect in the Few-Placebo Regime via Gaussian Processes
por: Uehara, Eichi
Publicado: (2026)
por: Uehara, Eichi
Publicado: (2026)
Machine-Learned Sampling of Conditioned Path Measures
por: Jiang, Qijia, et al.
Publicado: (2025)
por: Jiang, Qijia, et al.
Publicado: (2025)
Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation
por: Fu, Yi-Fu, et al.
Publicado: (2025)
por: Fu, Yi-Fu, et al.
Publicado: (2025)
Direct Bayesian Additive Regression Trees for Conditional Average Treatment Effects in Regression Discontinuity Designs
por: Kondo, Daisuke, et al.
Publicado: (2026)
por: Kondo, Daisuke, et al.
Publicado: (2026)
DeepBlip: Estimating Conditional Average Treatment Effects Over Time
por: Ma, Haorui, et al.
Publicado: (2025)
por: Ma, Haorui, et al.
Publicado: (2025)
Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence
por: Paillard, Joseph, et al.
Publicado: (2024)
por: Paillard, Joseph, et al.
Publicado: (2024)
Marginals Before Conditionals
por: Sahasrabudhe, Mihir
Publicado: (2026)
por: Sahasrabudhe, Mihir
Publicado: (2026)
Preference-based Conditional Treatment Effects and Policy Learning
por: Parnas, Dovid, et al.
Publicado: (2026)
por: Parnas, Dovid, et al.
Publicado: (2026)
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
por: Kato, Masahiro
Publicado: (2025)
por: Kato, Masahiro
Publicado: (2025)
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts
por: Kern, Christoph, et al.
Publicado: (2024)
por: Kern, Christoph, et al.
Publicado: (2024)
Sampling from Flow Language Models via Marginal-Conditioned Bridges
por: Azangulov, Iskander, et al.
Publicado: (2026)
por: Azangulov, Iskander, et al.
Publicado: (2026)
Robust and Agnostic Learning of Conditional Distributional Treatment Effects
por: Kallus, Nathan, et al.
Publicado: (2022)
por: Kallus, Nathan, et al.
Publicado: (2022)
Conditional Local Importance by Quantile Expectations
por: Bladen, Kelvyn K., et al.
Publicado: (2024)
por: Bladen, Kelvyn K., et al.
Publicado: (2024)
Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable
por: Kawakami, Yuta, et al.
Publicado: (2024)
por: Kawakami, Yuta, et al.
Publicado: (2024)
Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests
por: Blesch, Kristin, et al.
Publicado: (2025)
por: Blesch, Kristin, et al.
Publicado: (2025)
Conditional Distribution Quantization in Machine Learning
por: Delattre, Blaise, et al.
Publicado: (2025)
por: Delattre, Blaise, et al.
Publicado: (2025)
Double Machine Learning Methods for Estimating Average Treatment Effects: A Comparative Study
por: Tan, Xiaoqing, et al.
Publicado: (2022)
por: Tan, Xiaoqing, et al.
Publicado: (2022)
Model Averaging and Double Machine Learning
por: Ahrens, Achim, et al.
Publicado: (2024)
por: Ahrens, Achim, et al.
Publicado: (2024)
Robust Domain Generalization under Divergent Marginal and Conditional Distributions
por: Yeom, Jewon, et al.
Publicado: (2026)
por: Yeom, Jewon, et al.
Publicado: (2026)
Identification of Average Treatment Effects in Nonparametric Panel Models
por: Athey, Susan, et al.
Publicado: (2025)
por: Athey, Susan, et al.
Publicado: (2025)
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates
por: Wang, Baozhen, et al.
Publicado: (2025)
por: Wang, Baozhen, et al.
Publicado: (2025)
Joint Model and Data Sparsification via the Marginal Likelihood
por: Timans, Alexander, et al.
Publicado: (2026)
por: Timans, Alexander, et al.
Publicado: (2026)
Dynamic Local Average Treatment Effects
por: Sojitra, Ravi B., et al.
Publicado: (2024)
por: Sojitra, Ravi B., et al.
Publicado: (2024)
Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
por: Ballinari, Daniele, et al.
Publicado: (2024)
por: Ballinari, Daniele, et al.
Publicado: (2024)
Explaining Machine Learning Predictive Models through Conditional Expectation Methods
por: Ruiz-España, Silvia, et al.
Publicado: (2026)
por: Ruiz-España, Silvia, et al.
Publicado: (2026)
shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
por: Jullum, Martin, et al.
Publicado: (2025)
por: Jullum, Martin, et al.
Publicado: (2025)
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
por: Wang, Yuxin, et al.
Publicado: (2024)
por: Wang, Yuxin, et al.
Publicado: (2024)
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
por: Jain, Saksham, et al.
Publicado: (2026)
por: Jain, Saksham, et al.
Publicado: (2026)
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
por: Neopane, Ojash, et al.
Publicado: (2025)
por: Neopane, Ojash, et al.
Publicado: (2025)
Conditional Forecasting of Margin Calls using Dynamic Graph Neural Networks
por: Citterio, Matteo, et al.
Publicado: (2024)
por: Citterio, Matteo, et al.
Publicado: (2024)
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
por: Neopane, Ojash, et al.
Publicado: (2024)
por: Neopane, Ojash, et al.
Publicado: (2024)
Ejemplares similares
-
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
por: Shi, Pengfei, et al.
Publicado: (2024) -
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
por: Melnychuk, Valentyn, et al.
Publicado: (2025) -
Conditional Average Treatment Effect Estimation Under Hidden Confounders
por: Aloui, Ahmed, et al.
Publicado: (2025) -
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
por: Nagai, Tomoko, et al.
Publicado: (2024) -
Learning Conditional Averages
por: Bressan, Marco, et al.
Publicado: (2026)