Prof. Dr. Mathias Kraus

2022

• Bingler, J.A., Kraus, M., Leippold, M., & Webersinke, N. (2022). Cheap Talk and Cherry-Picking: What ClimateBert has to say on Corporate Climate Risk Disclosures. Finance Research Letters, 47, 102776. https://dx.doi.org/10.1016/j.frl.2022.102776
• Bingler, J.A., Kraus, M., Leippold, M., & Webersinke, N. (2022). Cheap Talk in Corporate Climate Commitments: The effectiveness of climate initiatives.
• Harl, M., Herchenbach, M., Kruschel, S., Hambauer, N., Zschech, P., & Kraus, M. (2022). A Light in the Dark: Deep Learning Practices for Industrial Computer Vision. In Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). Nürnberg, DE.
• Hershcovich, D., Webersinke, N., Kraus, M., Bingler, J.A., & Leippold, M. (2022). Towards Climate Awareness in NLP Research. In Proceedings of the EMNLP 2022: The 2022 Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, AE.
• Lorenz, R., Kraus, M., Wolf, H., Feuerriegel, S., & Netland, T.H. (2022). Selecting advanced analytics in manufacturing: a decision support model. Production Planning & Control. https://dx.doi.org/10.1080/09537287.2022.2126951
• Webersinke, N., Kraus, M., Bingler, J.A., & Leippold, M. (2022). ClimateBert: A Pretrained Language Model for Climate-Related Text. In Proceedings of the AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges. Arlington, VA, US.
• Zschech, P., Weinzierl, S., Hambauer, N., Zilker, S., & Kraus, M. (2022). GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints. In Proceedings of the 30th European Conference on Information Systems (pp. 1-18). Timisoara, RO: AISeL.
• Zueger, T., Schallmoser, S., Kraus, M., Saar-Tsechansky, M., Feuerriegel, S., & Stettler, C. (2022). Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes. Diabetes Technology & Therapeutics. https://dx.doi.org/10.1089/dia.2022.0210

2021

• Bingler, J.A., Kraus, M., & Leippold, M. (2021). Cheap Talk and Cherry-Picking: What ClimateBert has to say on Corporate Climate Risk Disclosures. Social Science Research Network. https://dx.doi.org/10.2139/ssrn.3796152
• Maag, B., Feuerriegel, S., Kraus, M., Saar-Tsechansky, M., & Züger, T. (2021). Modeling longitudinal dynamics of comorbidities. In ACM CHIL 2021 - Proceedings of the 2021 ACM Conference on Health, Inference, and Learning (pp. 222-235). Association for Computing Machinery, Inc.
• Ozyurt, Y., Kraus, M., Hatt, T., & Feuerriegel, S. (2021). AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 3452-3462). Virtual, SG: Association for Computing Machinery.
• la Torre, A.M.D., van Weenen, E., Kraus, M., Weiler, S., Feuerriegel, S., & Burden, A.M. (2021). A network analysis of drug combinations associated with acute generalized exanthematous pustulosis (AGEP). Journal of Clinical Medicine, 10(19). https://dx.doi.org/10.3390/jcm10194486

2020

• Ducci, F., Kraus, M., & Feuerriegel, S. (2020). Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 2666-2676). Association for Computing Machinery.
• Kraus, M., Feuerriegel, S., & Oztekin, A. (2020). Deep learning in business analytics and operations research: Models, applications and managerial implications. European Journal of Operational Research, 281(3), 628-641. https://dx.doi.org/10.1016/j.ejor.2019.09.018
• Maritsch, M., Föll, S., Lehmann, V., Bérubé, C., Kraus, M., Feuerriegel, S.,... Wortmann, F. (2020). Towards wearable-based hypoglycemia detection and warning in diabetes. In Conference on Human Factors in Computing Systems - Proceedings. Honolulu, HI, US: Association for Computing Machinery.
• Zueger, T., Gloor, M., Lehmann, V., Melmer, A., Kraus, M., Feuerriegel, S.,... Stettler, C. (2020). White coat adherence effect on glucose control in adult individuals with diabetes. Diabetes Research and Clinical Practice, 168. https://dx.doi.org/10.1016/j.diabres.2020.108392