Saved in:
| Main Author: | Uehara, Eichi |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.27473 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes
by: Uehara, Eichi
Published: (2026)
by: Uehara, Eichi
Published: (2026)
Stop Suppressing the Tail: Causal Inference for Extreme Events
by: Uehara, Eichi
Published: (2026)
by: Uehara, Eichi
Published: (2026)
The Unified Non-Convex Framework for Robust Causal Inference: Overcoming the Gaussian Barrier and Optimization Fragility
by: Uehara, Eichi
Published: (2025)
by: Uehara, Eichi
Published: (2025)
SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
by: Uehara, Eichi
Published: (2026)
by: Uehara, Eichi
Published: (2026)
Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation
by: Uehara, Eichi
Published: (2026)
by: Uehara, Eichi
Published: (2026)
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
by: Shi, Pengfei, et al.
Published: (2024)
by: Shi, Pengfei, et al.
Published: (2024)
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
by: Nagai, Tomoko, et al.
Published: (2024)
by: Nagai, Tomoko, et al.
Published: (2024)
Double Robust Bayesian Inference on Average Treatment Effects
by: Breunig, Christoph, et al.
Published: (2022)
by: Breunig, Christoph, et al.
Published: (2022)
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
by: Melnychuk, Valentyn, et al.
Published: (2025)
by: Melnychuk, Valentyn, et al.
Published: (2025)
Conditional Average Treatment Effect Estimation Under Hidden Confounders
by: Aloui, Ahmed, et al.
Published: (2025)
by: Aloui, Ahmed, et al.
Published: (2025)
Causal Clustering for Conditional Average Treatment Effects Estimation and Subgroup Discovery
by: Wang, Zilong, et al.
Published: (2025)
by: Wang, Zilong, et al.
Published: (2025)
Calibrating Transformers via Sparse Gaussian Processes
by: Chen, Wenlong, et al.
Published: (2023)
by: Chen, Wenlong, et al.
Published: (2023)
Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
by: Zhang, Yan, et al.
Published: (2026)
by: Zhang, Yan, et al.
Published: (2026)
ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging
by: Takaya, Eichi, et al.
Published: (2025)
by: Takaya, Eichi, et al.
Published: (2025)
Marginal and Conditional Importance Measures from Machine Learning Models and Their Relationship with Conditional Average Treatment Effect
by: Khan, Mohammad Kaviul Anam, et al.
Published: (2025)
by: Khan, Mohammad Kaviul Anam, et al.
Published: (2025)
Treatment Effects in Extreme Regimes
by: Aloui, Ahmed, et al.
Published: (2023)
by: Aloui, Ahmed, et al.
Published: (2023)
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
by: Huang, Yiyan, et al.
Published: (2024)
by: Huang, Yiyan, et al.
Published: (2024)
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates
by: Wang, Baozhen, et al.
Published: (2025)
by: Wang, Baozhen, et al.
Published: (2025)
Direct Bayesian Additive Regression Trees for Conditional Average Treatment Effects in Regression Discontinuity Designs
by: Kondo, Daisuke, et al.
Published: (2026)
by: Kondo, Daisuke, et al.
Published: (2026)
Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation
by: Fu, Yi-Fu, et al.
Published: (2025)
by: Fu, Yi-Fu, et al.
Published: (2025)
DeepBlip: Estimating Conditional Average Treatment Effects Over Time
by: Ma, Haorui, et al.
Published: (2025)
by: Ma, Haorui, et al.
Published: (2025)
SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes
by: Shen, Yishan, et al.
Published: (2025)
by: Shen, Yishan, et al.
Published: (2025)
Dynamic Local Average Treatment Effects
by: Sojitra, Ravi B., et al.
Published: (2024)
by: Sojitra, Ravi B., et al.
Published: (2024)
Calibrated Computation-Aware Gaussian Processes
by: Hegde, Disha, et al.
Published: (2024)
by: Hegde, Disha, et al.
Published: (2024)
Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable
by: Kawakami, Yuta, et al.
Published: (2024)
by: Kawakami, Yuta, et al.
Published: (2024)
Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
by: Ballinari, Daniele, et al.
Published: (2024)
by: Ballinari, Daniele, et al.
Published: (2024)
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts
by: Kern, Christoph, et al.
Published: (2024)
by: Kern, Christoph, et al.
Published: (2024)
A Bayesian Additive Regression Tree Model for Learning Conditional Average Treatment Effects in Regression Discontinuity Designs
by: Alcantara, Rafael, et al.
Published: (2025)
by: Alcantara, Rafael, et al.
Published: (2025)
Learning Conditional Averages
by: Bressan, Marco, et al.
Published: (2026)
by: Bressan, Marco, et al.
Published: (2026)
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
by: Neopane, Ojash, et al.
Published: (2025)
by: Neopane, Ojash, et al.
Published: (2025)
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
by: Neopane, Ojash, et al.
Published: (2024)
by: Neopane, Ojash, et al.
Published: (2024)
Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process
by: Williams, Bernardo, et al.
Published: (2026)
by: Williams, Bernardo, et al.
Published: (2026)
Conditioning Gaussian Processes on Almost Anything
by: Moss, Henry, et al.
Published: (2026)
by: Moss, Henry, et al.
Published: (2026)
Three Costs of Amortizing Gaussian Process Inference with Neural Processes
by: Young, Robin
Published: (2026)
by: Young, Robin
Published: (2026)
Instrumental and Proximal Causal Inference with Gaussian Processes
by: Zhang, Yuqi, et al.
Published: (2026)
by: Zhang, Yuqi, et al.
Published: (2026)
Sparse Orthogonal Variational Inference for Gaussian Processes
by: Shi, Jiaxin, et al.
Published: (2019)
by: Shi, Jiaxin, et al.
Published: (2019)
Amortized Variational Inference for Deep Gaussian Processes
by: Meng, Qiuxian, et al.
Published: (2024)
by: Meng, Qiuxian, et al.
Published: (2024)
Identification of Average Treatment Effects in Nonparametric Panel Models
by: Athey, Susan, et al.
Published: (2025)
by: Athey, Susan, et al.
Published: (2025)
Similar Items
-
Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes
by: Uehara, Eichi
Published: (2026) -
Stop Suppressing the Tail: Causal Inference for Extreme Events
by: Uehara, Eichi
Published: (2026) -
The Unified Non-Convex Framework for Robust Causal Inference: Overcoming the Gaussian Barrier and Optimization Fragility
by: Uehara, Eichi
Published: (2025) -
SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
by: Uehara, Eichi
Published: (2026) -
Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation
by: Uehara, Eichi
Published: (2026)