:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhan, Qishi, Yu, Cheng-Han, Chen, Yuchi, Dong, Zhikang, Guhaniyogi, Rajarshi
Format:	Preprint
Published:	2026
Subjects:	Methodology Artificial Intelligence
Online Access:	https://arxiv.org/abs/2602.07681
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Generative Modeling with Spatial and Network Images: An Explainable AI (XAI) Approach
by: Jeon, Yeseul, et al.
Published: (2025)

Uncertainty-Aware Neural Multivariate Geostatistics
by: Jeon, Yeseul, et al.
Published: (2026)

JASPER: Joint Bayesian Analysis of Spatial Expression via Regression
by: Dey, Pritam, et al.
Published: (2026)

Bayesian Data Sketching for Varying Coefficient Regression Models
by: Guhaniyogi, Rajarshi, et al.
Published: (2025)

Data Sketching and Stacking: A Confluence of Two Strategies for Predictive Inference in Gaussian Process Regressions with High-Dimensional Features
by: Gailliot, Samuel, et al.
Published: (2024)

Supervised Learning of Functional Outcomes with Predictors at Different Scales: A Functional Gaussian Process Approach
by: Andros, R. Jacob, et al.
Published: (2026)

Beyond False Discovery Rate: A Stepdown Group SLOPE Approach for Grouped Variable Selection
by: Zhang, Xuelin, et al.
Published: (2026)

Interpretable Deep Neural Network for Modeling Functional Surrogates
by: Jeon, Yeseul, et al.
Published: (2025)

Multivariate Conformal Selection
by: Bai, Tian, et al.
Published: (2025)

Practically Effective Adjustment Variable Selection in Causal Inference
by: Noda, Atsushi, et al.
Published: (2025)

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
by: Xie, Feng, et al.
Published: (2023)

Recover Experimental Data with Selection Bias using Counterfactual Logic
by: He, Jingyang, et al.
Published: (2025)

Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling
by: Dong, Jinzong, et al.
Published: (2024)

Multi-object Data Integration in the Study of Primary Progressive Aphasia
by: Gutierrez, Rene, et al.
Published: (2024)

Discovering and Reasoning of Causality in the Hidden World with Large Language Models
by: Liu, Chenxi, et al.
Published: (2024)

Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models
by: Guo, Xichen, et al.
Published: (2024)

Optimized Conformal Selection: Powerful Selective Inference After Conformity Score Optimization
by: Bai, Tian, et al.
Published: (2024)

Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies
by: Jeong, Hyunchai, et al.
Published: (2024)

Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation
by: Li, He, et al.
Published: (2025)

Robustifying and Selecting Cohort-Appropriate Prognostic Models under Distributional Shifts
by: Bertsimas, Dimitris, et al.
Published: (2026)

General sample size analysis for probabilities of causation: a delta method approach
by: Cheng, Tianyuan, et al.
Published: (2026)

Causal Unit Selection using Tractable Arithmetic Circuits
by: Huang, Haiying, et al.
Published: (2024)

Foundations of Structural Causal Models with Latent Selection
by: Chen, Leihao, et al.
Published: (2024)

Inferring the Most Similar Variable-length Subsequences between Multidimensional Time Series
by: Rattanakornphan, Thanadej, et al.
Published: (2025)

Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
by: Mahajan, Divyat, et al.
Published: (2022)

Constrained Identifiability of Causal Effects
by: Chen, Yizuo, et al.
Published: (2024)

Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
by: Shen, ChengAo, et al.
Published: (2024)

Towards a holistic understanding of Selection Bias for Causal Effect Identification
by: Qiu, Yiwen, et al.
Published: (2026)

A Generalized Genetic Random Field Method for the Genetic Association Analysis of Sequencing Data
by: Li, Ming, et al.
Published: (2025)

Optimizing Feature Selection in Causal Inference: A Three-Stage Computational Framework for Unbiased Estimation
by: Yang, Tianyu, et al.
Published: (2025)

Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
by: Hu, Jiuyun, et al.
Published: (2024)

Multi-Band Variable-Lag Granger Causality: A Unified Framework for Causal Time Series Inference across Frequencies
by: Sookkongwaree, Chakattrai, et al.
Published: (2025)

A Two-Stage Feature Selection Approach for Robust Evaluation of Treatment Effects in High-Dimensional Observational Data
by: Islam, Md Saiful, et al.
Published: (2021)

Probing the Information Theoretical Roots of Spatial Dependence Measures
by: Wang, Zhangyu, et al.
Published: (2024)

Can Large Language Models Help Experimental Design for Causal Discovery?
by: Li, Junyi, et al.
Published: (2025)

Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
by: Zhang, Zheyu, et al.
Published: (2025)

CafeMed: Causal Attention Fusion Enhanced Medication Recommendation
by: Ren, Kelin, et al.
Published: (2025)

Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives
by: Balakrishnan, Sivaraman, et al.
Published: (2025)

CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2026)

The Robustness of Differentiable Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2025)