Elias Bareinboim

43

Papers

124

Total Citations

Papers (43)

Experimental Design for Learning Causal Graphs with Latent Variables

Neural Causal Abstractions

Causally Aligned Curriculum Learning

Scores for Learning Discrete Causal Graphs with Unobserved Confounders

Counterfactual Identification Under Monotonicity Constraints

Reconciling Predictive and Statistical Parity: A Causal Approach

Transportable Representations for Domain Generalization

Fairness-Accuracy Trade-Offs: A Causal Perspective

Counterfactual Image Editing

Causal Transportability for Visual Recognition

Bandits with Unobserved Confounders: A Causal Approach

Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies

Towards Safe Policy Learning under Partial Identifiability: A Causal Approach

Causal Identification with Matrix Equations

The Causal-Neural Connection: Expressiveness, Learnability, and Inference

Sequential Causal Imitation Learning with Unobserved Confounders

Double Machine Learning Density Estimation for Local Treatment Effects with Instruments

Online Reinforcement Learning for Mixed Policy Scopes

Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness

Finding and Listing Front-door Adjustment Sets

Causal discovery from observational and interventional data across multiple environments

A Causal Framework for Decomposing Spurious Variations

Estimating Causal Effects Identifiable from a Combination of Observations and Experiments

Causal Fairness for Outcome Control

Nonparametric Identifiability of Causal Representations from Unknown Interventions

Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables

Counterfactual Data-Fusion for Online Reinforcement Learners

Budgeted Experiment Design for Causal Structure Learning

Sensitivity Analysis of Linear Structural Causal Models

Adjustment Criteria for Generalizing Experimental Findings

Causal Identification under Markov Equivalence: Completeness Results

Structural Causal Bandits: Where to Intervene?

Equality of Opportunity in Classification: A Causal Approach

Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets

Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes

Identification of Conditional Causal Effects under Markov Equivalence

Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions

Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe

Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning

General Transportability of Soft Interventions: Completeness Results

Causal Imitation Learning With Unobserved Confounders

Learning Causal Effects via Weighted Empirical Risk Minimization

Nested Counterfactual Identification from Arbitrary Surrogate Experiments