Calibrated Inference for the Conditional Average Treatment Effect in the Few-Placebo Regime via Gaussian Processes
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Uehara, Eichi |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes
par: Uehara, Eichi
Publié: (2026)
par: Uehara, Eichi
Publié: (2026)
Stop Suppressing the Tail: Causal Inference for Extreme Events
par: Uehara, Eichi
Publié: (2026)
par: Uehara, Eichi
Publié: (2026)
The Unified Non-Convex Framework for Robust Causal Inference: Overcoming the Gaussian Barrier and Optimization Fragility
par: Uehara, Eichi
Publié: (2025)
par: Uehara, Eichi
Publié: (2025)
SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
par: Uehara, Eichi
Publié: (2026)
par: Uehara, Eichi
Publié: (2026)
Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation
par: Uehara, Eichi
Publié: (2026)
par: Uehara, Eichi
Publié: (2026)
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
par: Kato, Masahiro
Publié: (2024)
par: Kato, Masahiro
Publié: (2024)
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
par: Shi, Pengfei, et autres
Publié: (2024)
par: Shi, Pengfei, et autres
Publié: (2024)
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
par: Melnychuk, Valentyn, et autres
Publié: (2025)
par: Melnychuk, Valentyn, et autres
Publié: (2025)
Conditional Average Treatment Effect Estimation Under Hidden Confounders
par: Aloui, Ahmed, et autres
Publié: (2025)
par: Aloui, Ahmed, et autres
Publié: (2025)
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
par: Nagai, Tomoko, et autres
Publié: (2024)
par: Nagai, Tomoko, et autres
Publié: (2024)
Double Robust Bayesian Inference on Average Treatment Effects
par: Breunig, Christoph, et autres
Publié: (2022)
par: Breunig, Christoph, et autres
Publié: (2022)
Causal Clustering for Conditional Average Treatment Effects Estimation and Subgroup Discovery
par: Wang, Zilong, et autres
Publié: (2025)
par: Wang, Zilong, et autres
Publié: (2025)
Calibrating Transformers via Sparse Gaussian Processes
par: Chen, Wenlong, et autres
Publié: (2023)
par: Chen, Wenlong, et autres
Publié: (2023)
Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
par: Zhang, Yan, et autres
Publié: (2026)
par: Zhang, Yan, et autres
Publié: (2026)
Marginal and Conditional Importance Measures from Machine Learning Models and Their Relationship with Conditional Average Treatment Effect
par: Khan, Mohammad Kaviul Anam, et autres
Publié: (2025)
par: Khan, Mohammad Kaviul Anam, et autres
Publié: (2025)
Treatment Effects in Extreme Regimes
par: Aloui, Ahmed, et autres
Publié: (2023)
par: Aloui, Ahmed, et autres
Publié: (2023)
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
par: Huang, Yiyan, et autres
Publié: (2024)
par: Huang, Yiyan, et autres
Publié: (2024)
ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging
par: Takaya, Eichi, et autres
Publié: (2025)
par: Takaya, Eichi, et autres
Publié: (2025)
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
par: Shi, Zhaoyang, et autres
Publié: (2024)
par: Shi, Zhaoyang, et autres
Publié: (2024)
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates
par: Wang, Baozhen, et autres
Publié: (2025)
par: Wang, Baozhen, et autres
Publié: (2025)
Direct Bayesian Additive Regression Trees for Conditional Average Treatment Effects in Regression Discontinuity Designs
par: Kondo, Daisuke, et autres
Publié: (2026)
par: Kondo, Daisuke, et autres
Publié: (2026)
Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation
par: Fu, Yi-Fu, et autres
Publié: (2025)
par: Fu, Yi-Fu, et autres
Publié: (2025)
SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes
par: Shen, Yishan, et autres
Publié: (2025)
par: Shen, Yishan, et autres
Publié: (2025)
Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable
par: Kawakami, Yuta, et autres
Publié: (2024)
par: Kawakami, Yuta, et autres
Publié: (2024)
Dynamic Local Average Treatment Effects
par: Sojitra, Ravi B., et autres
Publié: (2024)
par: Sojitra, Ravi B., et autres
Publié: (2024)
Calibrated Computation-Aware Gaussian Processes
par: Hegde, Disha, et autres
Publié: (2024)
par: Hegde, Disha, et autres
Publié: (2024)
Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
par: Ballinari, Daniele, et autres
Publié: (2024)
par: Ballinari, Daniele, et autres
Publié: (2024)
DeepBlip: Estimating Conditional Average Treatment Effects Over Time
par: Ma, Haorui, et autres
Publié: (2025)
par: Ma, Haorui, et autres
Publié: (2025)
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts
par: Kern, Christoph, et autres
Publié: (2024)
par: Kern, Christoph, et autres
Publié: (2024)
A Bayesian Additive Regression Tree Model for Learning Conditional Average Treatment Effects in Regression Discontinuity Designs
par: Alcantara, Rafael, et autres
Publié: (2025)
par: Alcantara, Rafael, et autres
Publié: (2025)
Learning Conditional Averages
par: Bressan, Marco, et autres
Publié: (2026)
par: Bressan, Marco, et autres
Publié: (2026)
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
par: Neopane, Ojash, et autres
Publié: (2025)
par: Neopane, Ojash, et autres
Publié: (2025)
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
par: Neopane, Ojash, et autres
Publié: (2024)
par: Neopane, Ojash, et autres
Publié: (2024)
Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process
par: Williams, Bernardo, et autres
Publié: (2026)
par: Williams, Bernardo, et autres
Publié: (2026)
Three Costs of Amortizing Gaussian Process Inference with Neural Processes
par: Young, Robin
Publié: (2026)
par: Young, Robin
Publié: (2026)
Instrumental and Proximal Causal Inference with Gaussian Processes
par: Zhang, Yuqi, et autres
Publié: (2026)
par: Zhang, Yuqi, et autres
Publié: (2026)
Sparse Orthogonal Variational Inference for Gaussian Processes
par: Shi, Jiaxin, et autres
Publié: (2019)
par: Shi, Jiaxin, et autres
Publié: (2019)
Amortized Variational Inference for Deep Gaussian Processes
par: Meng, Qiuxian, et autres
Publié: (2024)
par: Meng, Qiuxian, et autres
Publié: (2024)
Conditioning Gaussian Processes on Almost Anything
par: Moss, Henry, et autres
Publié: (2026)
par: Moss, Henry, et autres
Publié: (2026)
Erasure Coded Neural Network Inference via Fisher Averaging
par: Jhunjhunwala, Divyansh, et autres
Publié: (2024)
par: Jhunjhunwala, Divyansh, et autres
Publié: (2024)
Documents similaires
-
Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes
par: Uehara, Eichi
Publié: (2026) -
Stop Suppressing the Tail: Causal Inference for Extreme Events
par: Uehara, Eichi
Publié: (2026) -
The Unified Non-Convex Framework for Robust Causal Inference: Overcoming the Gaussian Barrier and Optimization Fragility
par: Uehara, Eichi
Publié: (2025) -
SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
par: Uehara, Eichi
Publié: (2026) -
Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation
par: Uehara, Eichi
Publié: (2026)