{"total":43,"rows":[{"id":"2310.15450","title":"General Identifiability and Achievability for Causal Representation Learning","created":"2023-10-24","cited_by_count":34,"area":null},{"id":"2310.13387","title":"Assumption violations in causal discovery and the robustness of score matching","created":"2023-10-20","cited_by_count":28,"area":null},{"id":"2306.10816","title":"$\\texttt{causalAssembly}$: Generating Realistic Production Data for Benchmarking Causal Discovery","created":"2023-06-19","cited_by_count":18,"area":null},{"id":"2402.18477","title":"Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes","created":"2024-02-28","cited_by_count":18,"area":null},{"id":"2310.18123","title":"Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling","created":"2023-10-27","cited_by_count":16,"area":null},{"id":"2406.14302","title":"Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning","created":"2024-06-20","cited_by_count":16,"area":null},{"id":"2407.18755","title":"Score matching through the roof: linear, nonlinear, and latent variables causal discovery","created":"2024-07-26","cited_by_count":10,"area":null},{"id":"2406.10481","title":"DCILP: A Distributed Approach for Large-Scale Causal Structure Learning","created":"2024-06-15","cited_by_count":8,"area":null},{"id":"2410.06407","title":"A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery","created":"2024-10-08","cited_by_count":7,"area":null},{"id":"2410.23620","title":"Identifiability Guarantees for Causal Disentanglement from Purely Observational Data","created":"2024-10-31","cited_by_count":7,"area":null},{"id":"2406.09177","title":"Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency","created":"2024-06-13","cited_by_count":6,"area":null},{"id":"2502.05122","title":"Distinguishing Cause from Effect with Causal Velocity Models","created":"2025-02-07","cited_by_count":6,"area":null},{"id":"2405.14496","title":"Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2604.23800","title":"Causal Representation Learning from General Environments under Nonparametric Mixing","created":"2026-04-26","cited_by_count":5,"area":null},{"id":"2305.18210","title":"Learning Causal Graphs via Monotone Triangular Transport Maps","created":"2023-05-26","cited_by_count":4,"area":null},{"id":"2310.14246","title":"Shortcuts for causal discovery of nonlinear models by score matching","created":"2023-10-22","cited_by_count":4,"area":null},{"id":"2403.03772","title":"AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs","created":"2024-03-06","cited_by_count":4,"area":null},{"id":"2309.01392","title":"Differentiable Bayesian Structure Learning with Acyclicity Assurance","created":"2023-09-04","cited_by_count":3,"area":null},{"id":"2411.05625","title":"Cross-validating causal discovery via Leave-One-Variable-Out","created":"2024-11-08","cited_by_count":3,"area":null},{"id":"2412.07469","title":"Score-matching-based Structure Learning for Temporal Data on Networks","created":"2024-12-10","cited_by_count":2,"area":null},{"id":"2510.24639","title":"Causal Ordering for Structure Learning from Time Series","created":"2025-10-28","cited_by_count":2,"area":null},{"id":"2607.11510","title":"DAG-FM: A Foundation Model for Causal Discovery under Heterogeneous Causal Mechanisms","created":"2026-07-13","cited_by_count":2,"area":null},{"id":"2410.11759","title":"LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2410.19870","title":"Causal Order Discovery based on Monotonic SCMs","created":"2024-10-24","cited_by_count":1,"area":null},{"id":"2501.14997","title":"Causal Discovery via Bayesian Optimization","created":"2025-01-25","cited_by_count":1,"area":null},{"id":"2502.17030","title":"Your Assumed DAG is Wrong and Here's How To Deal With It","created":"2025-02-24","cited_by_count":1,"area":null},{"id":"2601.16249","title":"Ordering-based Causal Discovery via Generalized Score Matching","created":"2026-01-22","cited_by_count":1,"area":null},{"id":"2604.25295","title":"Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians","created":"2026-04-28","cited_by_count":1,"area":null},{"id":"2605.22335","title":"Learning Causal Orderings for In-Context Tabular Prediction","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2607.03971","title":"Order-based Causal Discovery for Multistage Processes","created":"2026-07-04","cited_by_count":1,"area":null},{"id":"2507.16467","title":"Estimating Treatment Effects with Independent Component Analysis","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2510.13583","title":"On the Identifiability of Causal Graphs with the Invariance Principle","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2601.21014","title":"Efficient Causal Structure Learning via Modular Subgraph Integration","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2602.03353","title":"Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2602.15306","title":"Sparse Additive Model Pruning for Order-Based Causal Structure Learning","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2604.02488","title":"Causal-Audit: A Framework for Risk Assessment of Assumption Violations in Time-Series Causal Discovery","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2605.06288","title":"A Topological Sorting Criterion for Random Causal Directed Acyclic Graphs","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.26408","title":"Function-Valued Causal Influence in Nonlinear Time Series","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2609.24241","title":"Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.39326","title":"Discrete Score Matching Enables Causal Discovery from Count Data","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.02785","title":"Hold-Out Scoring for Efficient Gaussian DAG Learning","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.04291","title":"Local Fisher Information Enables Sparse Causal Discovery","created":"2026-10-03","cited_by_count":0,"area":null},{"id":"2610.18075","title":"Causal Discovery Under Hard Selection Bias: A New Robust Score-Matching Approach","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}