Direct Estimation of Differences in Causal Graphs. - Yuhao Wang 005; Chandler Squires; Anastasiya Belyaeva; Caroline Uhler (NeurIPS, 2018)

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery. - Raj Agrawal; Chandler Squires; Karren D. Yang; Karthikeyan Shanmugam; Caroline Uhler (AISTATS, 2019)

Size of Interventional Markov Equivalence Classes in random DAG models. - Dmitriy Katz; Karthikeyan Shanmugam; Chandler Squires; Caroline Uhler (AISTATS, 2019)

Ordering-Based Causal Structure Learning in the Presence of Latent Variables. - Daniel Irving Bernstein; Basil Saeed; Chandler Squires; Caroline Uhler (AISTATS, 2020)

Active Structure Learning of Causal DAGs via Directed Clique Trees. - Chandler Squires; Sara Magliacane; Kristjan H. Greenewald; Dmitriy Katz; Murat Kocaoglu; Karthikeyan Shanmugam (NeurIPS, 2020)

Permutation-Based Causal Structure Learning with Unknown Intervention Targets. - Chandler Squires; Yuhao Wang 005; Caroline Uhler (UAI, 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)

Efficient Permutation Discovery in Causal DAGs. - Chandler Squires; Joshua Amaniampong; Caroline Uhler (CoRR, 2020)

Matching a Desired Causal State via Shift Interventions. - Jiaqi Zhang; Chandler Squires; Caroline Uhler (NeurIPS, 2021)

DCI: learning causal differences between gene regulatory networks. - Anastasiya Belyaeva; Chandler Squires; Caroline Uhler (Bioinform., 2021)

Causal Imputation via Synthetic Interventions. - Chandler Squires; Dennis Shen; Anish Agarwal; Devavrat Shah; Caroline Uhler (CLeaR, 2022)

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors. - Chandler Squires; Annie Yun; Eshaan Nichani; Raj Agrawal; Caroline Uhler (CLeaR, 2022)

Linear Causal Disentanglement via Interventions. - Anna Seigal; Chandler Squires; Caroline Uhler (CoRR, 2022)

Linear Causal Disentanglement via Interventions. - Chandler Squires; Anna Seigal; Salil S. Bhate; Caroline Uhler (ICML, 2023)

Unpaired Multi-Domain Causal Representation Learning. - Nils Sturma; Chandler Squires; Mathias Drton; Caroline Uhler (NeurIPS, 2023)

Identifiability Guarantees for Causal Disentanglement from Soft Interventions. - Jiaqi Zhang; Kristjan H. Greenewald; Chandler Squires; Akash Srivastava; Karthikeyan Shanmugam; Caroline Uhler (NeurIPS, 2023)

Causal Structure Learning: A Combinatorial Perspective. - Chandler Squires; Caroline Uhler (Found. Comput. Math., 2023)

Active learning for optimal intervention design in causal models. - Jiaqi Zhang; Louis Cammarata; Chandler Squires; Themistoklis P. Sapsis; Caroline Uhler (Nat. Mac. Intell., 2023)

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models. - Alvaro Ribot; Chandler Squires; Caroline Uhler (CLeaR, 2024)

Synthetic Potential Outcomes for Mixtures of Treatment Effects. - Bijan Mazaheri; Chandler Squires; Caroline Uhler (CoRR, 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 and Causal Mixture Identifiability. - Bijan Mazaheri; Chandler Squires; Caroline Uhler (AISTATS, 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 (CLeaR, 2025)

Probably approximately correct high-dimensional causal effect estimation given a valid adjustment set. - Davin Choo; Chandler Squires; Arnab Bhattacharyya 001; David Sontag (CLeaR, 2025)

Knowledge-Enriched Machine Learning for Tabular Data. - Juyong Kim 002; Chandler Squires; Pradeep Ravikumar (NeuS, 2025)