Chandler Squires

According to our database1, Chandler Squires authored at least 20 papers between 2018 and 2024.

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Bibliography

2024
Synthetic Potential Outcomes for Mixtures of Treatment Effects.
CoRR, 2024

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models.
Proceedings of the Causal Learning and Reasoning, 2024

2023
Active learning for optimal intervention design in causal models.
Nat. Mac. Intell., October, 2023

Causal Structure Learning: A Combinatorial Perspective.
Found. Comput. Math., October, 2023

Identifiability Guarantees for Causal Disentanglement from Soft Interventions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unpaired Multi-Domain Causal Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linear Causal Disentanglement via Interventions.
Proceedings of the International Conference on Machine Learning, 2023

2022
Linear Causal Disentanglement via Interventions.
CoRR, 2022

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Causal Imputation via Synthetic Interventions.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
DCI: learning causal differences between gene regulatory networks.
Bioinform., 2021

Matching a Desired Causal State via Shift Interventions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Efficient Permutation Discovery in Causal DAGs.
CoRR, 2020

Active Structure Learning of Causal DAGs via Directed Clique Tree.
CoRR, 2020

Permutation-Based Causal Structure Learning with Unknown Intervention Targets.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Active Structure Learning of Causal DAGs via Directed Clique Trees.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Ordering-Based Causal Structure Learning in the Presence of Latent Variables.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Size of Interventional Markov Equivalence Classes in random DAG models.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Direct Estimation of Differences in Causal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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