mlsanityData to 7 Oct 2026

Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops

arXiv 2303.04038 ↗First posted 7 Mar 2023cs.AI cs.LGcited by 30

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Abstract (arXiv)

This paper presents an approach for identifying the root causes of collective anomalies given observational time series and an acyclic summary causal graph which depicts an abstraction of causal relations present in a dynamic system at its normal regime. The paper first shows how the problem of root cause identification can be divided into many independent subproblems by grouping related anomalies using d-separation. Further, it shows how, under this setting, some root causes can be found directly from the graph and from the time of appearance of anomalies. Finally, it shows, how the rest of the root causes can be found by comparing direct effects in the normal and in the anomalous regime. To this end, an adjustment set for identifying direct effects is introduced. Extensive experiments conducted on both simulated and real-world datasets demonstrate the effectiveness of the proposed method.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 6 of its 24 references that are in the map. First posted on arXiv 7 Mar 2023.

Builds on

6 of 24 references.

References · 6

  1. 2017Detecting causal associations in large nonlinear time series datasetscited by 240
  2. 2020Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasetscited by 136
  3. 2019Causal structure based root cause analysis of outlierscited by 65
  4. 2021Why did the distribution change?cited by 37
  5. 2021Entropy-based Discovery of Summary Causal Graphs in Time Seriescited by 9
  6. 2022NetRCA: An Effective Network Fault Cause Localization Algorithmcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 10; 2025: 10; 2026: 5.

30 papers.

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  1. 2023Causal Discovery from Temporal Data: An Overview and New Perspectivescited by 43
  2. 2023Case Studies of Causal Discovery from IT Monitoring Time Seriescited by 14
  3. 2023Identifiability of total effects from abstractions of time series causal graphscited by 13
  4. 2023Identifiability of Direct Effects from Summary Causal Graphscited by 12
  5. 2023Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithmscited by 8
  6. 2024Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confoundingcited by 8
  7. 2024Towards identifiability of micro total effects in summary causal graphs with latent confounding: extension of the front-door criterioncited by 5
  8. 2025Root Cause Analysis of Outliers in Unknown Cyclic Graphscited by 4
  9. 2025Identifying Macro Causal Effects in a C-DMG over ADMGscited by 3
  10. 2024On the Fly Detection of Root Causes from Observed Data with Application to IT Systemscited by 2
  11. 2024Counterfactual-based Root Cause Analysis for Dynamical Systemscited by 2
  12. 2024PORCA: Root Cause Analysis with Partially Observed Datacited by 2
18 more
  1. 2025Complete Characterization for Adjustment in Summary Causal Graphs of Time Seriescited by 2
  2. 2025Identifiability by common backdoor in summary causal graphs of time seriescited by 2
  3. 2025Identifying Macro Causal Effects in C-DMGs over DMGscited by 2
  4. 2025Regret-Based Federated Causal Discovery with Unknown Interventionscited by 2
  5. 2024Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphscited by 1
  6. 2024Causal reasoning in difference graphscited by 1
  7. 2024Industrial-Grade Time-Dependent Counterfactual Root Cause Analysis through the Unanticipated Point of Incipient Failure: a Proof of Conceptcited by 0
  8. 2024Root Cause Analysis Of Productivity Losses In Manufacturing Systems Utilizing Ensemble Machine Learningcited by 0
  9. 2024Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Datacited by 0
  10. 2025Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effectscited by 0
  11. 2025An Identifiable Cost-Aware Causal Decision-Making Framework Using Counterfactual Reasoningcited by 0
  12. 2025Orientability of Causal Relations in Time Series using Summary Causal Graphs and Faithful Distributionscited by 0
  13. 2025On Efficient Adjustment for Micro Causal Effects in Summary Causal Graphscited by 0
  14. 2026Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systemscited by 0
  15. 2026EvoCause: LLM-Guided Evolution of Causal Graphs for Root Cause Analysiscited by 0
  16. 2026Root cause analysis via difference graph discovery from linear time-series datacited by 0
  17. 2026Beyond Stationarity in Time Series: Discovering Causal Structures and Latent Regimes via Markov Blanketscited by 0
  18. 2026seq2cause: One Autoregressive Backbone, Four Causal Discovery Tasks in Event Sequencescited by 0