Image de couverture de livre

Scaling Causal Mediation for Complex Systems: A Framework for Root Cause Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Casadei, Alessandro, Bhaduri, Sreyoshi, Malshe, Rohit, Mullapudi, Pavan, Ratan, Raj, Pole, Ankush, Rakshit, Arkajit
Format:	Preprint
Publié:	2025
Sujets:	Methodology Artificial Intelligence Econometrics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Node-Level Financial Optimization in Demand Forecasting Through Dynamic Cost Asymmetry and Feedback Mechanism
par: Casadei, Alessandro, et autres
Publié: (2025)

OpComm: A Reinforcement Learning Framework for Adaptive Buffer Control in Warehouse Volume Forecasting
par: Fung, Wilson, et autres
Publié: (2025)

Balancing Weights for Causal Mediation Analysis
par: Kawato, Kentaro
Publié: (2025)

Causal Mediation Analysis with Multiple Mediators: A Simulation Approach
par: Zhou, Jesse, et autres
Publié: (2025)

Heterogeneous Responses to Continuous Treatments: A Cluster-Based Causal Framework
par: Cerqua, Augusto, et autres
Publié: (2024)

Extracting Mechanisms from Heterogeneous Effects: An Identification Strategy for Mediation Analysis
par: Fu, Jiawei
Publié: (2024)

Bootstrap Adaptive Lasso Solution Path Unit Root Tests
par: Arnold, Martin C., et autres
Publié: (2024)

Predictive Quantile Regression with Mixed Roots and Increasing Dimensions: The ALQR Approach
par: Fan, Rui, et autres
Publié: (2021)

Causal Inference for Spatial Treatments
par: Pollmann, Michael
Publié: (2020)

Using Experiments to Correct for Selection in Observational Studies
par: Athey, Susan, et autres
Publié: (2020)

Nonparametric Causal Decomposition of Group Disparities
par: Yu, Ang, et autres
Publié: (2023)

Heterogeneous Treatment Effects and Causal Mechanisms
par: Fu, Jiawei, et autres
Publié: (2024)

Does Regression Produce Representative Causal Rankings?
par: Lal, Apoorva
Publié: (2024)

Causal Inference in Counterbalanced Within-Subjects Designs
par: Ho, Justin, et autres
Publié: (2025)

Granger Causality in Expectiles: an M-vine copula test
par: Fuentes-Martínez, Roberto, et autres
Publié: (2026)

When Do Treatment Changes Identify Causal Effects?
par: Huber, Martin
Publié: (2026)

Non-parametric Causal Inference in Dynamic Thresholding Designs
par: Ghosh, Aditya, et autres
Publié: (2025)

Experimental Design For Causal Inference Through An Optimization Lens
par: Zhao, Jinglong
Publié: (2024)

Causal Inference for Experiments with Latent Outcomes: Key Results and Their Implications for Design and Analysis
par: Fu, Jiawei, et autres
Publié: (2025)

Relative Bias Under Imperfect Identification in Observational Causal Inference
par: Huang, Melody, et autres
Publié: (2025)

Graph Neural Networks for Causal Inference Under Network Confounding
par: Leung, Michael P., et autres
Publié: (2022)

Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
par: Chernozhukov, Victor, et autres
Publié: (2024)

Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models
par: Davezies, Laurent, et autres
Publié: (2021)

Reevaluating Causal Estimation Methods with Data from a Product Release
par: Young, Justin, et autres
Publié: (2026)

A Causal Inference Framework for Data Rich Environments
par: Abadie, Alberto, et autres
Publié: (2025)

Validating Causal Message Passing Against Network-Aware Methods on Real Experiments
par: Tan, Albert, et autres
Publié: (2026)

Causal Panel Analysis under Parallel Trends: Lessons from a Large Reanalysis Study
par: Chiu, Albert, et autres
Publié: (2023)

Scaling Reproducibility: An AI-Assisted Workflow for Large-Scale Replication and Reanalysis
par: Xu, Yiqing, et autres
Publié: (2026)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
par: Agarwal, Abhineet, et autres
Publié: (2023)

Coupling Designs for Randomized Experiments with Complex Treatments
par: Cytrynbaum, Max, et autres
Publié: (2026)

Large-Scale Curve Time Series with Common Stochastic Trends
par: Li, Degui, et autres
Publié: (2025)

Nonparametric Identification and Estimation of Causal Effects on Latent Outcomes
par: Fu, Jiawei, et autres
Publié: (2026)

Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
par: More, Sushant, et autres
Publié: (2024)

Sensitivity Analysis for Linear Estimators
par: Dorn, Jacob, et autres
Publié: (2023)

Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
par: Adedayo, S. A.
Publié: (2025)

Transmission Channel Analysis in Dynamic Models
par: Wegner, Enrico, et autres
Publié: (2024)

A Hybrid Framework Combining Autoregression and Common Factors for Matrix Time Series
par: Fan, Zhiyun, et autres
Publié: (2025)

Finite Population Identification and Design-Based Sensitivity Analysis
par: Kline, Brendan, et autres
Publié: (2025)

Likelihood-Based Ergodicity Transformations in Time Series Analysis
par: Britto, Anthony
Publié: (2026)

Regularizing Extrapolation in Causal Inference
par: Arbour, David, et autres
Publié: (2025)