Elias Bareinboim

Learning Invariances for Causal Abstraction Inference

Adapting, Fast and Slow: Transportable Circuits for Few-Shot Learning

Causal Canonical Modeling for Confounding Robust Treatment Evaluation

Epidemiology of Large Language Models: A Benchmark for Observational Distribution Knowledge

Counterfactual Rationality: A Causal Approach to Game Theory

Improving Causal Explanations

A Hierarchy of Graphical Models for Counterfactual Inferences

Counterfactual Graphical Models: Constraints and Inference

Counterfactual Realizability

Counterfactual Image Editing with Disentangled Causal Latent Space

Less Greedy Equivalence Search

Causal Discovery over Clusters of Variables in Markovian Systems

From Black-box to Causal-box: Towards Building More Interpretable Models

Confounding Robust Deep Reinforcement Learning: A Causal Approach

Structural Causal Bandits under Markov Equivalence

Causal Abstraction Inference under Lossy Representations

Eligibility Traces for Confounding Robust Off-Policy Evaluation: A Causal Approach

Automatic Reward Shaping from Confounded Offline Data