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Elias Bareinboim

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 12:40 AM AMS

29

papers

523

total citations

papers (29)

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

NEURIPS 2021arXiv

Causal Imitation Learning With Unobserved Confounders

NEURIPS 2020arXiv

Nonparametric Identifiability of Causal Representations from Unknown Interventions

NEURIPS 2023arXiv

Sequential Causal Imitation Learning with Unobserved Confounders

NEURIPS 2021arXiv

Causal Transportability for Visual Recognition

Nested Counterfactual Identification from Arbitrary Surrogate Experiments

NEURIPS 2021arXiv

Counterfactual Image Editing

Fairness-Accuracy Trade-Offs: A Causal Perspective

Neural Causal Abstractions

Causal Fairness for Outcome Control

NEURIPS 2023arXiv

Finding and Listing Front-door Adjustment Sets

NEURIPS 2022arXiv

Causally Aligned Curriculum Learning

Scores for Learning Discrete Causal Graphs with Unobserved Confounders

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

Counterfactual Identification Under Monotonicity Constraints

Reconciling Predictive and Statistical Parity: A Causal Approach

A Causal Framework for Decomposing Spurious Variations

NEURIPS 2023arXiv

General Transportability of Soft Interventions: Completeness Results

Causal discovery from observational and interventional data across multiple environments

Causal Identification with Matrix Equations

Learning Causal Effects via Weighted Empirical Risk Minimization

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

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

Transportable Representations for Domain Generalization

Estimating Causal Effects Identifiable from a Combination of Observations and Experiments

Towards Safe Policy Learning under Partial Identifiability: A Causal Approach

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