{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:12:25Z","timestamp":1760710345208,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030573201"},{"type":"electronic","value":"9783030573218"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-57321-8_28","type":"book-chapter","created":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T21:03:33Z","timestamp":1597871013000},"page":"499-515","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Property-Based Testing for Parameter Learning of Probabilistic Graphical Models"],"prefix":"10.1007","author":[{"given":"Anna","family":"Saranti","sequence":"first","affiliation":[]},{"given":"Behnam","family":"Taraghi","sequence":"additional","affiliation":[]},{"given":"Martin","family":"Ebner","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6786-5194","authenticated-orcid":false,"given":"Andreas","family":"Holzinger","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,18]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","unstructured":"On testing machine learning programs. J. Syst. Softw. 164, 110542 (2020). https:\/\/doi.org\/10.1016\/j.jss.2020.110542","DOI":"10.1016\/j.jss.2020.110542"},{"key":"28_CR2","unstructured":"Bishop, C.: Pattern Recognition and Machine Learning. Springer, New York (2006)"},{"key":"28_CR3","doi-asserted-by":"publisher","first-page":"110542","DOI":"10.1016\/j.jss.2020.110542","volume":"164","author":"HB Braiek","year":"2020","unstructured":"Braiek, H.B., Khomh, F.: On testing machine learning programs. J. Syst. Softw. 164, 110542 (2020)","journal-title":"J. Syst. Softw."},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Dutta, S., Legunsen, O., Huang, Z., Misailovic, S.: Testing probabilistic programming systems. In: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 574\u2013586 (2018)","DOI":"10.1145\/3236024.3236057"},{"key":"28_CR5","unstructured":"Grosse, R.B., Duvenaud, D.K.: Testing MCMC code. arXiv preprint. arXiv:1412.5218 (2014)"},{"key":"28_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-68282-2","volume-title":"Bayesian Networks and Decision Graphs","author":"FV Jensen","year":"2007","unstructured":"Jensen, F.V., Nielsen, T.D.: Bayesian Networks and Decision Graphs, 2nd edn. Springer, New York (2007)","edition":"2"},{"key":"28_CR7","volume-title":"Probabilistic Graphical Models: Principles and Techniques","author":"D Koller","year":"2009","unstructured":"Koller, D., Friedman, N.: Probabilistic Graphical Models: Principles and Techniques. MIT Press, Cambridge (2009)"},{"key":"28_CR8","volume-title":"Machine Learning: A Probabilistic Perspective","author":"KP Murphy","year":"2012","unstructured":"Murphy, K.P.: Machine Learning: A Probabilistic Perspective. MIT press, Cambridge (2012)"},{"key":"28_CR9","unstructured":"Nilsson, R.: ScalaCheck: the definitive guide. Artima (2014)"},{"key":"28_CR10","unstructured":"Okken, B.: Python Testing with Pytest: Simple, Rapid, Effective, and Scalable. Pragmatic Bookshelf (2017)"},{"key":"28_CR11","volume-title":"Practical Probabilistic Programming","author":"A Pfeffer","year":"2016","unstructured":"Pfeffer, A.: Practical Probabilistic Programming. Manning Publications, Greenwich (2016)"},{"key":"28_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1007\/978-3-030-29726-8_16","volume-title":"Machine Learning and Knowledge Extraction","author":"A Saranti","year":"2019","unstructured":"Saranti, A., Taraghi, B., Ebner, M., Holzinger, A.: Insights into learning competence through probabilistic graphical models. In: Holzinger, A., Kieseberg, P., Tjoa, A.M., Weippl, E. (eds.) CD-MAKE 2019. LNCS, vol. 11713, pp. 250\u2013271. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29726-8_16"},{"key":"28_CR13","unstructured":"Sharma, A., Wehrheim, H.: Testing monotonicity of machine learning models. arXiv:2002.12278 (2020)"},{"key":"28_CR14","doi-asserted-by":"crossref","unstructured":"Taraghi, B., Saranti, A., Legenstein, R., Ebner, M.: Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming. In: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, pp. 449\u2013453 (2016)","DOI":"10.1145\/2883851.2883895"},{"key":"28_CR15","unstructured":"Zhang, J.M., Harman, M., Ma, L., Liu, Y.: Machine learning testing: survey, landscapes and horizons. arXiv preprint arXiv:1906.10742 (2019)"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Extraction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-57321-8_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T06:52:43Z","timestamp":1724050363000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-57321-8_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030573201","9783030573218"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-57321-8_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"18 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CD-MAKE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Cross-Domain Conference for Machine Learning and Knowledge Extraction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dublin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ireland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cd-make2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cd-make.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}