mlsanityData to 7 Oct 2026

Causal structure based root cause analysis of outliers

arXiv 1912.02724 ↗First posted 5 Dec 2019stat.ML cs.LG math.STcited by 65

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Abstract (arXiv)

We describe a formal approach to identify 'root causes' of outliers observed in n variables X1,dots,Xn in a scenario where the causal relation between the variables is a known directed acyclic graph (DAG). To this end, we first introduce a systematic way to define outlier scores. Further, we introduce the concept of 'conditional outlier score' which measures whether a value of some variable is unexpected *given the value of its parents* in the DAG, if one were to assume that the causal structure and the corresponding conditional distributions are also valid for the anomaly. Finally, we quantify to what extent the high outlier score of some target variable can be attributed to outliers of its ancestors. This quantification is defined via Shapley values from cooperative game theory.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Dec 2019.

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Citing papers per year: 2021: 3; 2022: 9; 2023: 16; 2024: 9; 2025: 10; 2026: 18.

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  1. 2023Causal Order: The Key to Leveraging Imperfect Experts in Causal Inferencecited by 46
  2. 2023Counterfactual Identifiability of Bijective Causal Modelscited by 42
  3. 2022DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal modelscited by 40
  4. 2022Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Modelcited by 38
  5. 2023Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loopscited by 30
  6. 2024Root Cause Analysis of Outliers with Missing Structural Knowledgecited by 19
  7. 2023textttcausalAssembly: Generating Realistic Production Data for Benchmarking Causal Discoverycited by 18
  8. 2023Counterfactual (Non-)identifiability of Learned Structural Causal Modelscited by 17
  9. 2022Backtracking Counterfactualscited by 15
  10. 2023Targeted Reduction of Causal Modelscited by 15
  11. 2023Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Modelcited by 14
  12. 2023The PetShop Dataset -- Finding Causes of Performance Issues across Microservicescited by 14
38 more
  1. 2023AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challengescited by 13
  2. 2023Toward Falsifying Causal Graphs Using a Permutation-Based Testcited by 11
  3. 2022Identifying Patient-Specific Root Causes of Diseasecited by 8
  4. 2023Counterfactual Formulation of Patient-Specific Root Causes of Diseasecited by 8
  5. 2023Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Datacited by 7
  6. 2021Detecting Anomalous Event Sequences with Temporal Point Processescited by 6
  7. 2022Sample-Specific Root Causal Inference with Latent Variablescited by 6
  8. 2022On Root Cause Localization and Anomaly Mitigation through Causal Inferencecited by 6
  9. 2025Causal Additive Models with Unobserved Causal Paths and Backdoor Pathscited by 5
  10. 2025Counterfactual Identifiability via Dynamic Optimal Transportcited by 5
  11. 2025Unifying Explainable Anomaly Detection and Root Cause Analysis in Dynamical Systemscited by 4
  12. 2025Robust Root Cause Diagnosis using In-Distribution Interventionscited by 4
  13. 2025Root Cause Analysis of Outliers in Unknown Cyclic Graphscited by 4
  14. 2023Root Cause Explanation of Outliers under Noisy Mechanismscited by 3
  15. 2024Multiply-Robust Causal Change Attributioncited by 3
  16. 2024Causal Reasoning in Software Quality Assurance: A Systematic Reviewcited by 3
  17. 2024Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosiscited by 3
  18. 2025Toward Universal Laws of Outlier Propagationcited by 3
  19. 2026Graph-Free Root Cause Analysiscited by 3
  20. 2021More Than Words: Towards Better Quality Interpretations of Text Classifierscited by 2
  21. 2022Intrinsic Anomaly Detection for Multi-Variate Time Seriescited by 2
  22. 2022The Counterfactual-Shapley Value: Attributing Change in System Metricscited by 2
  23. 2023Beyond Single-Feature Importance with ICECREAMcited by 2
  24. 2024On the Fly Detection of Root Causes from Observed Data with Application to IT Systemscited by 2
  25. 2024Counterfactual-based Root Cause Analysis for Dynamical Systemscited by 2
  26. 2026Order-based Causal Discovery for Multistage Processescited by 1
  27. 2021Anomaly Mining -- Past, Present and Futurecited by 0
  28. 2022Testing Granger Non-Causality in Panels with Cross-Sectional Dependenciescited by 0
  29. 2023Estimation of Counterfactual Interventions under Uncertaintiescited by 0
  30. 2023Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Frameworkcited by 0
  31. 2024Industrial-Grade Time-Dependent Counterfactual Root Cause Analysis through the Unanticipated Point of Incipient Failure: a Proof of Conceptcited by 0
  32. 2024Root Cause Analysis Of Productivity Losses In Manufacturing Systems Utilizing Ensemble Machine Learningcited by 0
  33. 2024Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Datacited by 0
  34. 2025Learning Counterfactual Outcomes Under Rank Preservationcited by 0
  35. 2025An Identifiable Cost-Aware Causal Decision-Making Framework Using Counterfactual Reasoningcited by 0
  36. 2025Root Cause Analysis of Hydrogen Bond Separation in Spatio-Temporal Molecular Dynamics using Causal Modelscited by 0
  37. 2025Probabilities of Causation and Root Cause Analysis with Quasi-Markovian Modelscited by 0
  38. 2026Score-based Integrated Gradient for Root Cause Explanations of Outlierscited by 0

50 most cited of 65 All 65 (JSON)