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Causal graph

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Causal graph

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A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

CauseOccam: Learning Interpretable Abstract Representations in Reinforcement Learning Environments via Model Sparsity

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Causal inference in continuous time: an example on prostate cancer therapy

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables

The additive hazard estimator is consistent for continuous-time marginal structural models

Effect heterogeneity and variable selection for standardizing causal effects to a target population