{"total":26,"rows":[{"id":"2110.05690","title":"Partial Counterfactual Identification from Observational and Experimental Data","created":"2021-10-12","cited_by_count":64,"area":null},{"id":"2106.15563","title":"Learning latent causal graphs via mixture oracles","created":"2021-06-29","cited_by_count":55,"area":null},{"id":"2206.01152","title":"Causal Structure Learning: a Combinatorial Perspective","created":"2022-06-02","cited_by_count":46,"area":null},{"id":"2109.13471","title":"An Automated Approach to Causal Inference in Discrete Settings","created":"2021-09-28","cited_by_count":42,"area":null},{"id":"2504.11609","title":"Towards Interpretable Deep Generative Models via Causal Representation Learning","created":"2025-04-15","cited_by_count":13,"area":null},{"id":"2306.14351","title":"Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions","created":"2023-06-25","cited_by_count":11,"area":null},{"id":"2203.00161","title":"On Testability of the Front-Door Model via Verma Constraints","created":"2022-03-01","cited_by_count":8,"area":null},{"id":"2410.09600","title":"The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning","created":"2024-10-12","cited_by_count":8,"area":null},{"id":"2211.03984","title":"Causal Discovery in Linear Latent Variable Models Subject to Measurement Error","created":"2022-11-08","cited_by_count":7,"area":null},{"id":"2211.13447","title":"On the Complexity of Counterfactual Reasoning","created":"2022-11-24","cited_by_count":7,"area":null},{"id":"2307.03750","title":"When does the ID algorithm fail?","created":"2023-07-07","cited_by_count":7,"area":null},{"id":"2405.18314","title":"Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm","created":"2024-05-28","cited_by_count":5,"area":null},{"id":"2112.01847","title":"Causal Homotopy","created":"2021-09-20","cited_by_count":4,"area":null},{"id":"2209.06262","title":"Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory","created":"2022-09-13","cited_by_count":4,"area":null},{"id":"2603.04780","title":"Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning","created":"2026-03-05","cited_by_count":4,"area":null},{"id":"2202.13851","title":"The Causal Marginal Polytope for Bounding Treatment Effects","created":"2022-02-28","cited_by_count":3,"area":null},{"id":"2208.11077","title":"Categoroids: Universal Conditional Independence","created":"2022-08-23","cited_by_count":3,"area":null},{"id":"2207.02917","title":"On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property","created":"2022-07-06","cited_by_count":2,"area":null},{"id":"2406.09049","title":"Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams","created":"2024-06-10","cited_by_count":1,"area":null},{"id":"2507.16107","title":"Recursive Equations For Imputation Of Missing Not At Random Data With Sparse Pattern Support","created":"2025-07-21","cited_by_count":1,"area":null},{"id":"2212.08981","title":"A Layered Architecture for Universal Causality","created":"2022-12-18","cited_by_count":0,"area":null},{"id":"2305.14632","title":"Supermodular Rank: Set Function Decomposition and Optimization","created":"2023-05-24","cited_by_count":0,"area":null},{"id":"2505.18410","title":"On Theoretical Identifiability of Discrete Latent Causal Graphical Models","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2512.11919","title":"A fine-grained look at causal effects in causal spaces","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2607.13883","title":"Verifying formulas for interventional distributions","created":"2026-07-15","cited_by_count":0,"area":null},{"id":"2607.23439","title":"A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models","created":"2026-07-26","cited_by_count":0,"area":null}],"next_cursor":null}