Cover Image

Cross-World Assumption and Refining Prediction Intervals for Individual Treatment Effects

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bodik, Juraj, Huang, Yaxuan, Yu, Bin
Format:	Preprint
Published:	2025
Subjects:	Methodology Statistics Theory Machine Learning 62A01 G.3
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Retrospective Counterfactual Prediction by Conditioning on the Factual Outcome: A Cross-World Approach
by: Bodik, Juraj
Published: (2026)

Granger Causality in Extremes
by: Bodik, Juraj, et al.
Published: (2024)

Structural restrictions in local causal discovery: identifying direct causes of a target variable
by: Bodik, Juraj, et al.
Published: (2023)

Efficiency of nonparametric e-tests
by: Vovk, Vladimir, et al.
Published: (2022)

Factor Informed Double Deep Learning For Average Treatment Effect Estimation
by: Fan, Jianqing, et al.
Published: (2025)

On relative universality, regression operator, and conditional independence
by: Li, Bing, et al.
Published: (2025)

Kernel-based estimators for functional causal effects
by: Raykov, Yordan P., et al.
Published: (2025)

An Approximation Based Theory of Linear Regression
by: Davies, Laurie
Published: (2024)

Conditionality principle under unconstrained randomness
by: Vovk, Vladimir
Published: (2024)

Exchangeability and randomness for infinite and finite sequences
by: Vovk, Vladimir
Published: (2025)

Conformal Prediction = Bayes?
by: Datta, Jyotishka, et al.
Published: (2025)

Nonparametric Estimation in Uniform Deconvolution and Interval Censoring
by: Groeneboom, Piet, et al.
Published: (2025)

Nonparametric Least Squares Estimators for Interval Censoring
by: Groeneboom, Piet
Published: (2025)

Causal discovery under mean independence and linearity
by: Mesters, Geert, et al.
Published: (2026)

Causal Discovery for Linear Non-Gaussian Models with Disjoint Cycles
by: Drton, Mathias, et al.
Published: (2025)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)

Efficient adjustment for complex covariates: Gaining efficiency with DOPE
by: Christgau, Alexander Mangulad, et al.
Published: (2024)

Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments
by: Zhang, Yikun, et al.
Published: (2025)

What the Jeffreys-Lindley Paradox Really Is: Correcting a Persistent Misconception
by: Lovric, Miodrag M.
Published: (2025)

On the Identifiability of Tensor Ranks via Prior Predictive Matching
by: da Silva, Eliezer, et al.
Published: (2025)

Enhanced Survival Trees
by: Zhou, Ruiwen, et al.
Published: (2025)

Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning
by: Gu, Yihong, et al.
Published: (2024)

CINDES: Classification induced neural density estimator and simulator
by: Dai, Dehao, et al.
Published: (2025)

The Projected Covariance Measure for assumption-lean variable significance testing
by: Lundborg, Anton Rask, et al.
Published: (2022)

Local Fréchet regression with toroidal predictors
by: Im, Chang Jun, et al.
Published: (2026)

On Efficient Inference of Causal Effects with Multiple Mediators
by: Wei, Haoyu, et al.
Published: (2024)

Statistical Unlearning of Distributions: A Hypothesis Testing Approach
by: Pandey, Aaradhya, et al.
Published: (2026)

On the Existence of Unbiased Hypothesis Tests: An Algebraic Approach
by: McCormack, Andrew
Published: (2025)

Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects
by: Ji, Wenlong, et al.
Published: (2023)

Adjusted Similarity Measures and a Violation of Expectations
by: Lippitt, William L., et al.
Published: (2026)

M-estimation under Two-Phase Multiwave Sampling with Applications to Prediction-Powered Inference
by: Kluger, Dan M., et al.
Published: (2026)

Structure-Preserving Nonlinear Sufficient Dimension Reduction for Tensors
by: Lin, Dianjun, et al.
Published: (2025)

Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
by: Wang, Kaizheng
Published: (2023)

Batched Single-Index Global Multi-Armed Bandits with Covariates
by: Arya, Sakshi, et al.
Published: (2025)

Nonparametric f-Modeling for Empirical Bayes Inference with Unequal and Unknown Variances
by: Zhao, Zhigen, et al.
Published: (2026)

Physics-informed machine learning: A mathematical framework with applications to time series forecasting
by: Doumèche, Nathan
Published: (2025)

Functional Partial Least-Squares: Adaptive Estimation and Inference
by: Babii, Andrii, et al.
Published: (2024)

Nonparametric inference under shape constraints: past, present and future
by: Samworth, Richard J.
Published: (2025)

Assessing replication success via skeptical mixture priors
by: Consonni, Guido, et al.
Published: (2023)

Robust spectral clustering with rank statistics
by: Cape, Joshua, et al.
Published: (2024)