{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T05:52:55Z","timestamp":1776405175210,"version":"3.51.2"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032238320","type":"print"},{"value":"9783032238337","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-23833-7_9","type":"book-chapter","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T05:10:53Z","timestamp":1776402653000},"page":"113-125","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["NTS-DAGMA: A Score-Based Causal Discovery for\u00a0Anomaly Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2894-6319","authenticated-orcid":false,"given":"Navin","family":"Vincent","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4178-5257","authenticated-orcid":false,"given":"Abhishek","family":"Srinivasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8577-6745","authenticated-orcid":false,"given":"Anders","family":"Holst","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3272-4145","authenticated-orcid":false,"given":"Sepideh","family":"Pashami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,18]]},"reference":[{"key":"9_CR1","doi-asserted-by":"crossref","unstructured":"Bello, K., Aragam, B., Ravikumar, P.: DAGMA: learning DAGs via m-matrices and a log-determinant acyclicity characterization. In: Advances in Neural Information Processing Systems, vol. 35, pp. 8226\u20138239 (2022)","DOI":"10.52202\/068431-0598"},{"issue":"3","key":"9_CR2","first-page":"404","volume":"35","author":"P B\u00fchlmann","year":"2020","unstructured":"B\u00fchlmann, P.: Invariance, causality and robustness. Stat. Sci. 35(3), 404\u2013426 (2020)","journal-title":"Stat. Sci."},{"issue":"3","key":"9_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. ACM Comput. Surv. (CSUR) 41(3), 1\u201358 (2009)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"11","key":"9_CR4","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1038\/s42256-020-00257-z","volume":"2","author":"R Geirhos","year":"2020","unstructured":"Geirhos, R., et al.: Shortcut learning in deep neural networks. Nat. Mach. Intell. 2(11), 665\u2013673 (2020)","journal-title":"Nat. Mach. Intell."},{"key":"9_CR5","unstructured":"Han, X., Absar, S., Zhang, L., Yuan, S.: Root cause analysis of anomalies in multivariate time series through granger causal discovery. In: The Thirteenth International Conference on Learning Representations (2025)"},{"issue":"2","key":"9_CR6","doi-asserted-by":"publisher","first-page":"20170016","DOI":"10.1515\/jci-2017-0016","volume":"6","author":"C Heinze-Deml","year":"2018","unstructured":"Heinze-Deml, C., Peters, J., Meinshausen, N.: Invariant causal prediction for nonlinear models. J. Causal Infer. 6(2), 20170016 (2018)","journal-title":"J. Causal Infer."},{"issue":"12","key":"9_CR7","doi-asserted-by":"publisher","first-page":"10466","DOI":"10.1109\/TPAMI.2024.3443141","volume":"46","author":"M Jin","year":"2024","unstructured":"Jin, M., et al.: A survey on graph neural networks for time series: forecasting, classification, imputation, and anomaly detection. IEEE Trans. Pattern Anal. Mach. Intell. 46(12), 10466\u201310485 (2024). https:\/\/doi.org\/10.1109\/TPAMI.2024.3443141","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Mathur, A.P., Tippenhauer, N.O.: SWaT: a water treatment testbed for research and training on ICS security. In: 2016 International Workshop on Cyber-Physical Systems for Smart Water Networks (CySWater), pp. 31\u201336. IEEE (2016)","DOI":"10.1109\/CySWater.2016.7469060"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Meli, D.: Explainable online unsupervised anomaly detection for cyber-physical systems via causal discovery from time series. In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 4120\u20134125. IEEE (2024)","DOI":"10.1109\/CASE59546.2024.10711445"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Pearl, J.: Causality. Cambridge University Press (2009)","DOI":"10.1017\/CBO9780511803161"},{"key":"9_CR11","unstructured":"Pearl, J., Mackenzie, D.: The Book of Why: The New Science of Cause and Effect. Basic Books (2018)"},{"issue":"5","key":"9_CR12","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1111\/rssb.12167","volume":"78","author":"J Peters","year":"2016","unstructured":"Peters, J., B\u00fchlmann, P., Meinshausen, N.: Causal inference by using invariant prediction: identification and confidence intervals. J. R. Stat. Soc. Ser. B Stat Methodol. 78(5), 947\u20131012 (2016)","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."},{"key":"9_CR13","unstructured":"Peters, J., Janzing, D., Sch\u00f6lkopf, B.: Elements of Causal Inference: Foundations and Learning Algorithms. The MIT Press (2017)"},{"key":"9_CR14","unstructured":"Runge, J.: Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. In: Conference on Uncertainty in Artificial Intelligence, pp. 1388\u20131397. PMLR (2020)"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Runge, J., Nowack, P., Kretschmer, M., Flaxman, S., Sejdinovic, D.: Detecting and quantifying causal associations in large nonlinear time series datasets. Sci. Adv. 5(11), eaau4996 (2019)","DOI":"10.1126\/sciadv.aau4996"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Spirtes, P., Glymour, C.N., Scheines, R.: Causation, Prediction, and Search. MIT Press (2000)","DOI":"10.7551\/mitpress\/1754.001.0001"},{"key":"9_CR17","unstructured":"Sun, X., Schulte, O., Liu, G., Poupart, P.: NTS-NOTEARS: learning nonparametric DBNs with prior knowledge. In: International Conference on Artificial Intelligence and Statistics (2021). https:\/\/api.semanticscholar.org\/CorpusID:252907768"},{"issue":"4","key":"9_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3527154","volume":"55","author":"MJ Vowels","year":"2022","unstructured":"Vowels, M.J., Camgoz, N.C., Bowden, R.: D\u2019ya like DAGs? A survey on structure learning and causal discovery. ACM Comput. Surv. 55(4), 1\u201336 (2022)","journal-title":"ACM Comput. Surv."},{"key":"9_CR19","unstructured":"Xiao, X., Shen, B., Yue, X.: Causality-informed anomaly detection in partially observable sensor networks: moving beyond correlations. arXiv preprint arXiv:2507.09742 (2025)"},{"key":"9_CR20","unstructured":"Yang, W., Zhang, K., Hoi, S.C.: Causality-based multivariate time series anomaly detection. CoRR (2022)"}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XXIV"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-23833-7_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T05:11:00Z","timestamp":1776402660000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-23833-7_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032238320","9783032238337"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-23833-7_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"18 April 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leiden","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 April 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ida2026.liacs.nl\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}