:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Wenxin, Pan, Weishen, Gan, Kyra, Wang, Fei
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.14284
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Doubly Debiased Longitudinal Effect Estimation with ICE G-Computation
by: Chen, Wenxin, et al.
Published: (2026)

MOSIC: Model-Agnostic Optimal Subgroup Identification with Multi-Constraint for Improved Reliability
by: Chen, Wenxin, et al.
Published: (2025)

Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
by: Maasch, Jacqueline, et al.
Published: (2023)

Federated Causal Inference in Healthcare: Methods, Challenges, and Applications
by: Li, Haoyang, et al.
Published: (2025)

Integrating Causal DAGs in Deep RL: Activating Minimal Markovian States with Multi-Order Exposure
by: Xu, Jiamin, et al.
Published: (2026)

Local Causal Discovery for Structural Evidence of Direct Discrimination
by: Maasch, Jacqueline, et al.
Published: (2024)

LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery
by: Hiremath, Sujai, et al.
Published: (2024)

When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery
by: Meier, Dominik, et al.
Published: (2025)

Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding
by: Xu, Jiamin, et al.
Published: (2026)

Joint Analysis of Single-Cell Data across Cohorts with Missing Modalities
by: Arriola, Marianne, et al.
Published: (2024)

Efficient Imputation for Patch-based Missing Single-cell Data via Cluster-regularized Optimal Transport
by: Liu, Yuyu, et al.
Published: (2026)

Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
by: Cho, Brian, et al.
Published: (2023)

Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
by: Rajendran, Suraj, et al.
Published: (2023)

Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits
by: Cho, Brian, et al.
Published: (2024)

Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams
by: Cho, Brian, et al.
Published: (2024)

Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
by: Hiremath, Sujai, et al.
Published: (2024)

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces
by: Yu, Shixing, et al.
Published: (2026)

CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies
by: Cho, Brian M, et al.
Published: (2024)

Dynamic Causal Structure Discovery and Causal Effect Estimation
by: Wang, Jianian, et al.
Published: (2025)

From Guess2Graph: When and How Can Unreliable Experts Safely Boost Causal Discovery in Finite Samples?
by: Hiremath, Sujai, et al.
Published: (2025)

Contextual Bandits with Budgeted Information Reveal
by: Gan, Kyra, et al.
Published: (2023)

Online Uniform Sampling: Randomized Learning-Augmented Approximation Algorithms with Application to Digital Health
by: Liu, Xueqing, et al.
Published: (2024)

From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvement
by: Xu, Jiamin, et al.
Published: (2025)

Local Causal Discovery for Estimating Causal Effects
by: Gupta, Shantanu, et al.
Published: (2023)

Clustering by Denoising: Latent plug-and-play diffusion for single-cell data
by: Meier, Dominik, et al.
Published: (2025)

Causal Multi-Label Feature Selection in Federated Setting
by: Song, Yukun, et al.
Published: (2024)

Policy Optimization with Smooth Guidance Learned from State-Only Demonstrations
by: Wang, Guojian, et al.
Published: (2023)

Estimating Causal Effects from Learned Causal Networks
by: Raichev, Anna, et al.
Published: (2024)

Learning Causality for Longitudinal Data
by: Bouchattaoui, Mouad EL
Published: (2025)

Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models
by: Wang, Jiankun, et al.
Published: (2024)

CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
by: Balazadeh, Vahid, et al.
Published: (2025)

Estimating the Causal Effects of T Cell Receptors
by: Weinstein, Eli N., et al.
Published: (2024)

Optimal Adjustment Sets for Nonparametric Estimation of Weighted Controlled Direct Effect
by: Lin, Ruiyang, et al.
Published: (2025)

Estimating Aleatoric Uncertainty in the Causal Treatment Effect
by: Xu, Liyuan, et al.
Published: (2026)

DAG-aware Transformer for Causal Effect Estimation
by: Liu, Manqing, et al.
Published: (2024)

Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing
by: Nagalapatti, Lokesh, et al.
Published: (2024)

Optimizing Graph Causal Classification Models: Estimating Causal Effects and Addressing Confounders
by: Job, Simi, et al.
Published: (2026)

Neighborhood Adaptive Estimators for Causal Inference under Network Interference
by: Belloni, Alexandre, et al.
Published: (2022)

Causal Clustering for Conditional Average Treatment Effects Estimation and Subgroup Discovery
by: Wang, Zilong, et al.
Published: (2025)

The Amenability Framework: Rethinking Causal Ordering Without Estimating Causal Effects
by: Fernández-Loría, Carlos, et al.
Published: (2025)