Cover Image

Causal Influence Maximization with Steady-State Guarantees

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cao, Renjie, Yan, Zhuoxin, Su, Xinyan, Zhang, Zhiheng
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Individualized Causal Effects under Network Interference with Combinatorial Treatments
by: Lu, Yunping, et al.
Published: (2026)

Causal Representation Learning with Optimal Compression under Complex Treatments
by: Liang, Wanting, et al.
Published: (2026)

Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization
by: Su, Xinyan, et al.
Published: (2023)

Convex Mixed-Integer Programming for Causal Additive Models with Optimization and Statistical Guarantees
by: Zhang, Xiaozhu, et al.
Published: (2025)

Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
by: Gao, Jiacan, et al.
Published: (2026)

Common-Individual Embedding for Dynamic Networks with Temporal Group Structure
by: Bai, Hairi, et al.
Published: (2025)

Orthogonal Uplift Learning with Permutation-Invariant Representations for Combinatorial Treatments
by: Su, Xinyan, et al.
Published: (2026)

Propensity Score Analysis with Guaranteed Subgroup Balance
by: Li, Yan, et al.
Published: (2024)

Robust Inference for Causal Mediation Analysis of Recurrent Event Data
by: Chen, Yan-Lin, et al.
Published: (2023)

Leader-Follower Identification Methodology for Non-Lane Disciplined Heterogeneous Traffic Using Steady State Features
by: Eldhose, Susan, et al.
Published: (2025)

Network Model Averaging Prediction for Latent Space Models by K-Fold Edge Cross-Validation
by: Zhang, Yan, et al.
Published: (2025)

Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
by: Wang, Yunfeng, et al.
Published: (2026)

Adjusting auxiliary variables under approximate neighborhood interference
by: Lu, Xin, et al.
Published: (2024)

Leveraging Shared Factor Structures for Enhanced Matrix Completion with Nonconvex Penalty Regularization
by: A, Yuanhong, et al.
Published: (2025)

Heterogeneity-Aware Federated Causal Inference Leveraging Effect-Measure Transportability
by: Cao, Siqi, et al.
Published: (2025)

Conformal Prediction With Conditional Guarantees
by: Gibbs, Isaac, et al.
Published: (2023)

Causal Spatial Quantile Regression
by: Gong, Yan, et al.
Published: (2025)

Flexible semiparametric modeling with application to Causal Inference
by: Ren, Kun, et al.
Published: (2026)

Iterative Data Curation with Theoretical Guarantees
by: Yrjänäinen, Väinö, et al.
Published: (2025)

Causal attribution with confidence
by: Zhang, Ping, et al.
Published: (2025)

Detecting Imprinting and Maternal Effects Using Monte Carlo Expectation Maximization Algorithm
by: Aavani, Pooya, et al.
Published: (2023)

Steady Continuous Monitoring is (Just Barely) Impossible for Tests of Unbounded Length
by: Bax, Eric, et al.
Published: (2024)

Transfer learning under latent space model
by: Fang, Kuangnan, et al.
Published: (2025)

Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments
by: Zhu, Hongtao, et al.
Published: (2024)

Guarantees for Comprehensive Simulation Assessment of Statistical Methods
by: Yang, James, et al.
Published: (2022)

A Causal Framework for Evaluating Jointly Longitudinal Outcomes and Surrogate Markers: A State-Space Approach
by: Santos Jr., Silvaneo V. dos, et al.
Published: (2026)

Statistical and Causal Robustness for Causal Null Hypothesis Tests
by: Yang, Junhui, et al.
Published: (2023)

Estimation and Inference for Causal Explainability
by: Zhang, Weihan, et al.
Published: (2025)

Causality and extremes
by: Chavez-Demoulin, Valérie, et al.
Published: (2024)

Challenges in Statistics: A Dozen Challenges in Causality and Causal Inference
by: Cinelli, Carlos, et al.
Published: (2025)

Monte Carlo Expectation-Maximization algorithm to detect imprinting and maternal effects for discordant sib-pair data
by: Herath, Ruwani, et al.
Published: (2023)

Data-Driven Influence Functions for Optimization-Based Causal Inference
by: Jordan, Michael I., et al.
Published: (2022)

Causal-learn: Causal Discovery in Python
by: Zheng, Yujia, et al.
Published: (2023)

Embarrassingly Causal: Causal Use of Associational Data in Magic The Gathering Drafts
by: Ramos, Mark Louie F., et al.
Published: (2026)

Multivariate Causal Effects: a Bayesian Causal Regression Factor Model
by: Zorzetto, Dafne, et al.
Published: (2025)

Causal Inference on Sequential Treatments via Tensor Completion
by: Gao, Chenyin, et al.
Published: (2025)

Feasible Fusion: Constrained Joint Estimation under Structural Non-Overlap
by: Du, Yuxi, et al.
Published: (2026)

Causal Stability Selection
by: Bargagli-Stoffi, Falco J., et al.
Published: (2026)

Generative Causal Inference
by: Nareklishvili, Maria, et al.
Published: (2023)

Geodesic Causal Inference
by: Kurisu, Daisuke, et al.
Published: (2024)