Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence. 2024;38(13):14388-14396. doi:10.1609/aaai.v38i13.29352
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Amiri A, Tavana M, Arman H. An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction. Internet of Things. 2024;25. doi:10.1016/j.iot.2023.101027
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Habernal I, Faber D, Recchia N, et al. Mining legal arguments in court decisions. Artificial Intelligence and Law. Published online 2023. doi:10.1007/s10506-023-09361-y
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Fumagalli F, Muschalik M, Hüllermeier E, Hammer B. Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning. Published online 2023. doi:10.1007/s10994-023-06385-y
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Artelt A, Visser R, Hammer B. “I do not know! but why?”10.1016/j.neucom.2023.126722__— Local model-agnostic example-based explanations of reject. Neurocomputing. 2023;558. doi:10.1016/j.neucom.2023.126722
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Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. Computers in Human Behavior Reports. 2023;9. doi:10.1016/j.chbr.2022.100258
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Groß A, Schütze C, Brandt M, Wrede B, Richter B. RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. Frontiers in Robotics and AI. 2023;10. doi:10.3389/frobt.2023.1245501
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Leffrang D. AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization. In: International Conference on Information Systems. ; 2023.
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Fumagalli F, Muschalik M, Hüllermeier E, Hammer B. Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning. 2023;112(12):4863-4903. doi:10.1007/s10994-023-06385-y
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Vieluf S, Hasija T, Kuschel M, Reinsberger C, Loddenkemper T. Developing a deep canonical correlation-based technique for seizure prediction. Expert Systems with Applications. 2023;234. doi:10.1016/j.eswa.2023.120986
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Tavana M, Khalili Nasr A, Ahmadabadi AB, Amiri AS, Mina H. An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks. Internet of Things. 2023;22. doi:10.1016/j.iot.2023.100786
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Tavana M, Soltanifar M, Santos-Arteaga FJ, Sharafi H. Analytic hierarchy process and data envelopment analysis: A match made in heaven. Expert Systems with Applications. 2023;223. doi:10.1016/j.eswa.2023.119902
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Santos-Arteaga FJ, Di Caprio D, Tavana M, Tena EC. A Credibility and Strategic Behavior Approach in Hesitant Multiple Criteria Decision-Making With Application to Sustainable Transportation. IEEE Transactions on Fuzzy Systems. 2023;31(2):460-474. doi:10.1109/tfuzz.2022.3188875
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Tirkolaee EB, Torkayesh AE, Tavana M, Goli A, Simic V, Ding W. An integrated decision support framework for resilient vaccine supply chain network design. Engineering Applications of Artificial Intelligence. 2023;126. doi:10.1016/j.engappai.2023.106945
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Mahdiraji HA, Tavana M, Rezayar A. A Game-Theoretic Framework for Analyzing the Impact of Social Responsibility and Supply Chain Profitability. Cybernetics and Systems. 2023;54(1):104-137. doi:10.1080/01969722.2022.2055402
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Kucklick J-P. Visual Interpretability of Image-based Real Estate Appraisal. In: 55th Annual Hawaii International Conference on System Sciences (HICSS-55). ; 2022.
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Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In: Wirtschaftsinformatik 2022 Proceedings. ; 2022.
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Meyer M, Fichtler T, Koldewey C, Dumitrescu R. Potentials and challenges of analyzing use phase data in product planning of manufacturing companies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 2022;36. doi:10.1017/s0890060421000408
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Hoffmann C, Thommes K. Seizing the Opportunity for Automation—How Traffic Density Determines Truck Drivers’ Use of Cruise Control. IEEE Transactions on Human-Machine Systems. Published online 2022:1-11. doi:10.1109/thms.2022.3212335
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Rohlfing K, Altvater-Mackensen N, Caruana N, et al. Social/dialogical roles of social robots in supporting children’s learning of language and literacy—A review and analysis of innovative roles. Frontiers in Robotics and AI. 2022;9. doi:10.3389/frobt.2022.971749
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Schade R, Kenter T, Elgabarty H, et al. Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms. Parallel Computing. 2022;111. doi:10.1016/j.parco.2022.102920
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Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. Computers in Human Behavior Reports. 2022;9. doi:10.1016/j.chbr.2022.100258
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Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. Computers in Human Behavior Reports. Published online 2022. doi:10.1016/j.chbr.2022.100258
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Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. Computers in Human Behavior Reports. 2022;9. doi:10.1016/j.chbr.2022.100258
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Muschalik M, Fumagalli F, Hammer B, Hüllermeier E. Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz. 2022;36(3-4):211-224. doi:10.1007/s13218-022-00766-6
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Schmid U, Wrede B. What is Missing in XAI So Far? KI - Künstliche Intelligenz. 2022;36(3-4):303-315. doi:10.1007/s13218-022-00786-2
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Schmid U, Wrede B. Explainable AI. KI - Künstliche Intelligenz. 2022;36(3-4):207-210. doi:10.1007/s13218-022-00788-0
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Wrede B. AI: Back to the Roots? KI - Künstliche Intelligenz. 2022;36(2):117-120. doi:10.1007/s13218-022-00773-7
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Fisher JB, Lohmer V, Kern F, Barthlen W, Gaus S, Rohlfing K. Exploring Monological and Dialogical Phases in Naturally Occurring Explanations. KI - Künstliche Intelligenz. 2022;36(3-4):317-326. doi:10.1007/s13218-022-00787-1
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Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz. 2022;36(3-4):211-224. doi:10.1007/s13218-022-00766-6
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Turhan A-Y. A Double Take at Conferences: The Hybrid Format. KI - Künstliche Intelligenz. 2022;36(1):1-4. doi:10.1007/s13218-022-00758-6
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Tavana M, Shaabani A, Di Caprio D, Bonyani A. A novel Interval Type-2 Fuzzy best-worst method and combined compromise solution for evaluating eco-friendly packaging alternatives. Expert Systems with Applications. 2022;200. doi:10.1016/j.eswa.2022.117188
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Höper L. Developing and Evaluating the Concept Data Awareness for K12 Computing Education. In: 21st Koli Calling International Conference on Computing Education Research. Koli Calling ’21. Association for Computing Machinery; 2021. doi:10.1145/3488042.3490509
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Bernijazov R, Dicks A, Dumitrescu R, et al. A Meta-Review on Artiû01cial Intelligence in Product Creation. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21). ; 2021.
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Stieglitz S, Möllmann (Frick) NRJ, Mirbabaie M, Hofeditz L, Ross B. Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality. International Journal of Management Practice. Published online 2021.
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Gölz CJ, Mora K, Rudisch J, et al. Classification of visuomotor tasks based on electroencephalographic data depends on age-related differences in brain activity patterns. Neural Networks. 2021;142:363-374. doi:10.1016/j.neunet.2021.04.029
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Goelz C, Mora K, Rudisch J, et al. Classification of visuomotor tasks based on electroencephalographic data depends on age-related differences in brain activity patterns. Neural Networks. 2021;142:363-374. doi:10.1016/j.neunet.2021.04.029
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Mahmood Y, Meier A. Parameterised complexity of model checking and satisfiability in propositional dependence logic. Annals of Mathematics and Artificial Intelligence. 2021;90(2-3):271-296. doi:10.1007/s10472-021-09730-w
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Schlichtig M, Opel SA, Budde L, Schulte C. Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material. In: Jasut E, Pozdniakov S, eds. ISSEP 2019 - 12th International Conference on Informatics in Schools: Situation, Evaluation and Perspectives, Local Proceedings. Vol 12. ; 2019:65-73.
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Klowait N. The quest for appropriate models of human-likeness: anthropomorphism in media equation research. AI &; SOCIETY. 2017;33(4):527-536. doi:10.1007/s00146-017-0746-z
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Habernal I, Gurevych I. Argumentation Mining in User-Generated Web Discourse. Computational Linguistics. 2016;43(1):125-179. doi:10.1162/coli_a_00276
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Borgwardt S, Mailis T, Peñaloza R, Turhan A-Y. Answering Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies. Journal on Data Semantics. 2016;5(2):55-75. doi:10.1007/s13740-015-0055-y
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Borgwardt S, Mailis T, Peñaloza R, Turhan A-Y. Answering Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies. Journal on Data Semantics. 2016;5(2):55-75. doi:10.1007/s13740-015-0055-y
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Baraté A, Haus G, Ludovico LA, Mauro DA. IEEE 1599 for Live Musical and Theatrical Performances. Journal of Multimedia. 2012;7(2). doi:10.4304/jmm.7.2.170-178
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Klöpper B, Sondermann-Wölke C, Romaus C, Vöcking H. Probabilistic planning integrated in a multi-level dependability concept for mechatronic systems. In: Computational Intelligence in Control and Automation, 2009. CICA 2009. IEEE Symposium On. ; 2009:104-111. doi:10.1109/CICA.2009.4982790
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