{"total":24,"rows":[{"id":"2105.11839","title":"DiBS: Differentiable Bayesian Structure Learning","created":"2021-05-25","cited_by_count":106,"area":null},{"id":"2206.01665","title":"BaCaDI: Bayesian Causal Discovery with Unknown Interventions","created":"2022-06-03","cited_by_count":26,"area":null},{"id":"2207.08603","title":"Abstraction between Structural Causal Models: A Review of Definitions and Properties","created":"2022-07-18","cited_by_count":15,"area":null},{"id":"2208.10981","title":"Causal Entropy Optimization","created":"2022-08-23","cited_by_count":13,"area":null},{"id":"2211.14897","title":"Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions","created":"2022-11-27","cited_by_count":12,"area":null},{"id":"2405.16225","title":"Local Causal Structure Learning in the Presence of Latent Variables","created":"2024-05-25","cited_by_count":11,"area":null},{"id":"2208.05949","title":"Valid Inference After Causal Discovery","created":"2022-08-11","cited_by_count":10,"area":null},{"id":"2503.07302","title":"When Selection Meets Intervention: Additional Complexities in Causal Discovery","created":"2025-03-10","cited_by_count":10,"area":null},{"id":"2110.07064","title":"Variance Minimization in the Wasserstein Space for Invariant Causal Prediction","created":"2021-10-13","cited_by_count":5,"area":null},{"id":"2302.05380","title":"On the Interventional Kullback-Leibler Divergence","created":"2023-02-10","cited_by_count":5,"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":"2309.12833","title":"Model-based causal feature selection for general response types","created":"2023-09-22","cited_by_count":3,"area":null},{"id":"2410.02844","title":"CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series","created":"2024-10-03","cited_by_count":3,"area":null},{"id":"2412.11850","title":"Causal Invariance Learning via Efficient Nonconvex Optimization","created":"2024-12-16","cited_by_count":2,"area":null},{"id":"2509.25800","title":"Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data","created":"2025-09-30","cited_by_count":2,"area":null},{"id":"2211.03846","title":"Federated Causal Discovery From Interventions","created":"2022-11-07","cited_by_count":1,"area":null},{"id":"2608.28245","title":"I-FLOP: Fast Learning of Order and Parents from Interventional Data","created":"2026-08-28","cited_by_count":1,"area":null},{"id":"2311.04636","title":"Learning Linear Gaussian Polytree Models with Interventions","created":"2023-11-08","cited_by_count":0,"area":null},{"id":"2409.12797","title":"Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing","created":"2024-09-19","cited_by_count":0,"area":null},{"id":"2503.19554","title":"Causal Bayesian Optimization with Unknown Graphs","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2603.02204","title":"Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2606.06288","title":"Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2607.11816","title":"Relaxing Faithfulness with Intervention-Only Causal Discovery","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2608.12640","title":"Interpretable Causal Discovery via Causal-Effect Constraints","created":"2026-08-12","cited_by_count":0,"area":null}],"next_cursor":null}