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Representing the Quality of Crime Scenarios in a Bayesian Network.

, , , and . JURIX, volume 279 of Frontiers in Artificial Intelligence and Applications, page 131-140. IOS Press, (2015)

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Exploiting Evidence-dependent Sensitivity Bounds., and . UAI, page 485-492. AUAI Press, (2005)From Qualitative to Quantitative Probabilistic Networks., and . UAI, page 422-429. Morgan Kaufmann, (2002)When in Doubt ... Be Indecisive., , , and . ECSQARU, volume 5590 of Lecture Notes in Computer Science, page 518-529. Springer, (2009)On Intercausal Interactions in Probabilistic Relational Models., , and . ISIPTA, volume 103 of Proceedings of Machine Learning Research, page 327-329. PMLR, (2019)Representing the Quality of Crime Scenarios in a Bayesian Network., , , and . JURIX, volume 279 of Frontiers in Artificial Intelligence and Applications, page 131-140. IOS Press, (2015)Demonstration of a structure-guided approach to capturing bayesian reasoning about legal evidence in argumentation., , , , and . ICAIL, page 233-234. ACM, (2015)Building Bayesian networks for legal evidence with narratives: a case study evaluation., , , and . Artif. Intell. Law, 22 (4): 375-421 (2014)Discovering the Rationale of Decisions: Experiments on Aligning Learning and Reasoning., , and . XAILA@ICAIL, volume 3168 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Same-Decision Probability: Threshold Robustness and Application to Explanation.. PGM, volume 72 of Proceedings of Machine Learning Research, page 368-379. PMLR, (2018)Advances in Probabilistic Graphical Models, , and . volume 214/2007 of Studies in Fuzziness and Soft Computing, chapter Sensitivity Analysis of Probabilistic Networks, page 103--124. Springer Berlin / Heidelberg, (2007)