Chandler Squires

According to our database, Chandler Squires authored at least 25 papers between 2018 and 2025.

Collaborative distances:

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

2025

Knowledge-Enriched Machine Learning for Tabular Data.

Juyong Kim, Chandler Squires, Pradeep Ravikumar

Proceedings of the International Conference on Neuro-symbolic Systems, 2025

Probably approximately correct high-dimensional causal effect estimation given a valid adjustment set.

Davin Choo, Chandler Squires, Arnab Bhattacharyya, David Sontag

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications.

Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad K, Karen Sachs, Alexandre Drouin, Dhanya Sridhar

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

Synthetic Potential Outcomes and Causal Mixture Identifiability.

Bijan Mazaheri, Chandler Squires, Caroline Uhler

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications.

Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad P. Kording, Karen Sachs, Alexandre Drouin, Dhanya Sridhar

CoRR, 2024

Synthetic Potential Outcomes for Mixtures of Treatment Effects.

Bijan Mazaheri, Chandler Squires, Caroline Uhler

CoRR, 2024

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models.

Alvaro Ribot, Chandler Squires, Caroline Uhler

Proceedings of the Causal Learning and Reasoning, 2024

2023

Active learning for optimal intervention design in causal models.

Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler

Nat. Mac. Intell., October, 2023

Causal Structure Learning: A Combinatorial Perspective.

Chandler Squires, Caroline Uhler

Found. Comput. Math., October, 2023

Identifiability Guarantees for Causal Disentanglement from Soft Interventions.

Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

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.

Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linear Causal Disentanglement via Interventions.

Chandler Squires, Anna Seigal, Salil S. Bhate, Caroline Uhler

Proceedings of the International Conference on Machine Learning, 2023

2022

Linear Causal Disentanglement via Interventions.

Anna Seigal, Chandler Squires, Caroline Uhler

CoRR, 2022

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors.

Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Causal Imputation via Synthetic Interventions.

Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

DCI: learning causal differences between gene regulatory networks.

Anastasiya Belyaeva, Chandler Squires, Caroline Uhler

Bioinform., 2021

Matching a Desired Causal State via Shift Interventions.

Jiaqi Zhang, Chandler Squires, Caroline Uhler

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.

Chandler Squires, Joshua Amaniampong, Caroline Uhler

CoRR, 2020

Active Structure Learning of Causal DAGs via Directed Clique Tree.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

CoRR, 2020

Permutation-Based Causal Structure Learning with Unknown Intervention Targets.

Chandler Squires, Yuhao Wang, Caroline Uhler

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Active Structure Learning of Causal DAGs via Directed Clique Trees.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

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.

Daniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Size of Interventional Markov Equivalence Classes in random DAG models.

Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery.

Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Direct Estimation of Differences in Causal Graphs.

Yuhao Wang, Chandler Squires, Anastasiya Belyaeva, Caroline Uhler

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018