17 Publikationen

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  • [17]
    2025 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 3001554
    Suffian, M., et al., 2025. The role of user feedback in enhancing understanding and trust in counterfactual explanations for explainable AI. International Journal of Human-Computer Studies, : 103484.
    PUB | DOI
     
  • [16]
    2025 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 3001286
    Lüdemann, R., Schulz, A., & Kuhl, U., 2025. Generation Gap or Diffusion Trap? How Age Affects the Detection of Personalized AI-Generated Images. In H. Plácido da Silva & P. Cipresso, eds. Computer-Human Interaction Research and Applications. 8th International Conference, CHIRA 2024, Porto, Portugal, November 21–22, 2024, Proceedings, Part II. Communications in Computer and Information Science. no.2371 Cham: Springer Nature Switzerland, pp. 359-381.
    PUB | DOI
     
  • [15]
    2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2993468
    Kuhl, U., 2024. Shaping Trustworthy AI: An Introduction to This Issue. In U. Kuhl, ed. Proceedings of the DataNinja sAIOnARA 2024 Conference. no.2024 Bielefeld: BieColl, pp. 1-9.
    PUB | DOI | Download (ext.)
     
  • [14]
    2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2991660
    Suffian, M., et al., 2024. CL-XAI: Toward Enriched Cognitive Learning with Explainable Artificial Intelligence. In A. Aldini, ed. Software Engineering and Formal Methods. SEFM 2023 Collocated Workshops. CIFMA 2023 and OpenCERT 2023, Eindhoven, The Netherlands, November 6–10, 2023, Revised Selected Papers. Lecture Notes in Computer Science. no.14568 Cham: Springer , pp. 5-27.
    PUB | DOI | WoS
     
  • [13]
    2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2991552
    Rüttgers, S., Kuhl, U., & Paaßen, B., 2024. Automatic Matchmaking in Two-Versus-Two Sports. In B. Paaßen & C. Demmans Epp, eds. Proceedings of the 17th International Conference on Educational Data Mining. International Educational Data Mining Society, pp. 458--468.
    PUB | DOI | Download (ext.)
     
  • [12]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2983795
    Kuhl, U., Artelt, A., & Hammer, B., 2023. For Better or Worse: The Impact of Counterfactual Explanations’ Directionality on User Behavior in xAI. In L. Longo, ed. Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III. Communications in Computer and Information Science. Cham: Springer Nature Switzerland, pp. 280-300.
    PUB | DOI | WoS
     
  • [11]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969734 OA
    Kuhl, U., Artelt, A., & Hammer, B., 2023. Let's go to the Alien Zoo: Introducing an experimental framework to study usability of counterfactual explanations for machine learning. Frontiers in Computer Science, 5: 1087929.
    PUB | PDF | DOI | Download (ext.) | WoS | arXiv
     
  • [10]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2983759
    Koundouri, P., et al., 2023. Behavioral Economics and Neuroeconomics of Environmental Values. Annual Review of Resource Economics, 15(1), p 153-176.
    PUB | DOI | Download (ext.) | WoS
     
  • [9]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969736
    Kuhl, U., Artelt, A., & Hammer, B., 2022. Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting. In 2022 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM, pp. 2125-2137.
    PUB | DOI | Download (ext.)
     
  • [8]
    2022 | Report | Veröffentlicht | PUB-ID: 2965622 OA
    Hammer, B., et al., 2022. Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, Bielefeld: Univ. Bielefeld, Forschungsinstitut für Kognition und Robotik.
    PUB | PDF | DOI
     
  • [7]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2961871 OA
    Kuhl, U., Sobotta, S., & Skeide, M.A., 2021. Mathematical learning deficits originate in early childhood from atypical development of a frontoparietal brain network. PLOS Biology, 19(9): e3001407.
    PUB | PDF | DOI | WoS | PubMed | Europe PMC
     
  • [6]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959418
    Göpfert, J.P., et al., 2021. Intuitiveness in Active Teaching. IEEE Transactions on Human-Machine Systems, , p 1-10.
    PUB | DOI | WoS
     
  • [5]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2953387 OA
    Shim, M., et al., 2021. Resting-State Functional Connectivity in Mathematical Expertise. Brain Sciences, 11(4): 430.
    PUB | PDF | DOI | WoS | PubMed | Europe PMC
     
  • [4]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2938847
    Kuhl, U., et al., 2020. Early cortical surface plasticity relates to basic mathematical learning. NeuroImage, 204: 116235.
    PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
     
  • [3]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2941258
    Kuhl, U., et al., 2020. The emergence of dyslexia in the developing brain. NeuroImage, 211: 116633.
    PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
     
  • [2]
    2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2938846
    Jeon, H.-A., Kuhl, U., & Friederici, A.D., 2019. Mathematical expertise modulates the architecture of dorsal and cortico-thalamic white matter tracts. Scientific Reports, 9(1): 6825.
    PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
     
  • [1]
    2019 | Dissertation | PUB-ID: 2938928 OA
    Kuhl, U., 2019. The brain basis of emerging literacy and numeracy skills. Longitudinal neuroimaging evidence from kindergarten to primary school, Leipzig: Universität Leipzig.
    PUB | PDF
     

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