Juan D. Correa

According to our database, Juan D. Correa authored at least 13 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Counterfactual Transportability: A Formal Approach.

Juan D. Correa, Sanghack Lee, Elias Bareinboim

Proceedings of the International Conference on Machine Learning, 2022

On Pearl's Hierarchy and the Foundations of Causal Inference.

Elias Bareinboim, Juan D. Correa, Duligur Ibeling, Thomas Icard

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021

Nested Counterfactual Identification from Arbitrary Surrogate Experiments.

Juan D. Correa, Sanghack Lee, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

General Transportability of Soft Interventions: Completeness Results.

Juan D. Correa, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

General Transportability - Synthesizing Observations and Experiments from Heterogeneous Domains.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Identifiability from a Combination of Observations and Experiments.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Calculus for Stochastic Interventions: Causal Effect Identification and Surrogate Experiments.

Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

General Identifiability with Arbitrary Surrogate Experiments.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

From Statistical Transportability to Estimating the Effect of Stochastic Interventions.

Juan D. Correa, Elias Bareinboim

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Adjustment Criteria for Generalizing Experimental Findings.

Juan D. Correa, Jin Tian, Elias Bareinboim

Proceedings of the 36th International Conference on Machine Learning, 2019

Identification of Causal Effects in the Presence of Selection Bias.

Juan D. Correa, Jin Tian, Elias Bareinboim

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Generalized Adjustment Under Confounding and Selection Biases.

Juan D. Correa, Jin Tian, Elias Bareinboim

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Causal Effect Identification by Adjustment under Confounding and Selection Biases.

Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017