| Decision support from financial disclosures with deep neural networks and transfer learning M Kraus, S Feuerriegel Decision Support Systems 104, 38-48, 2017 | 285 | 2017 |
| Deep learning for affective computing: Text-based emotion recognition in decision support B Kratzwald, S Ilić, M Kraus, S Feuerriegel, H Prendinger Decision Support Systems 115, 24-35, 2018 | 250* | 2018 |
| Deep learning in business analytics and operations research: Models, applications and managerial implications M Kraus, S Feuerriegel, A Oztekin European Journal of Operational Research 281 (3), 628-641, 2020 | 239 | 2020 |
| Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences M Kraus, S Feuerriegel Decision Support Systems 125, 113100, 2019 | 96 | 2019 |
| Cheap talk and cherry-picking: What climatebert has to say on corporate climate risk disclosures JA Bingler, M Kraus, M Leippold, N Webersinke Finance Research Letters 47, 102776, 2022 | 73 | 2022 |
| Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees M Kraus, S Feuerriegel Expert Systems with Applications 118, 65-79, 2019 | 64 | 2019 |
| Climatebert: A pretrained language model for climate-related text N Webersinke, M Kraus, JA Bingler, M Leippold arXiv preprint arXiv:2110.12010, 2021 | 33 | 2021 |
| Cascade-LSTM: A tree-structured neural classifier for detecting misinformation cascades F Ducci, M Kraus, S Feuerriegel (KDD '20) Proceedings of the 26th ACM SIGKDD International Conference on …, 2020 | 26 | 2020 |
| Towards wearable-based hypoglycemia detection and warning in diabetes M Maritsch, S Föll, V Lehmann, C Bérubé, M Kraus, S Feuerriegel, ... Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing …, 2020 | 20 | 2020 |
| AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units Y Oezyurt, M Kraus, T Hatt, S Feuerriegel (KDD '21) Proceedings of the 27th ACM SIGKDD International Conference on …, 2021 | 18 | 2021 |
| Improving heart rate variability measurements from consumer smartwatches with machine learning M Maritsch, C Bérubé, M Kraus, V Lehmann, T Züger, S Feuerriegel, ... Adjunct Proceedings of the 2019 ACM International Joint Conference on …, 2019 | 14 | 2019 |
| Towards climate awareness in NLP research D Hershcovich, N Webersinke, M Kraus, JA Bingler, M Leippold (EMNLP '22) Proceedings of the 2022 Conference on Empirical Methods in …, 2022 | 11 | 2022 |
| Bringing advanced analytics to manufacturing: a systematic mapping H Wolf, R Lorenz, M Kraus, S Feuerriegel, TH Netland Advances in Production Management Systems. Production Management for the …, 2019 | 11 | 2019 |
| Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching M Kraus, S Feuerriegel (KDD '19) Proceedings of the 25th ACM SIGKDD International Conference on …, 2019 | 10 | 2019 |
| Cheap talk in corporate climate commitments: The effectiveness of climate initiatives JA Bingler, M Kraus, M Leippold, N Webersinke Available at SSRN 3998435, 2022 | 8 | 2022 |
| A network analysis of drug combinations associated with acute generalized exanthematous pustulosis (AGEP) A Martinez-De la Torre, E van Weenen, M Kraus, S Weiler, S Feuerriegel, ... Journal of Clinical Medicine 10 (19), 4486, 2021 | 7 | 2021 |
| GAM (e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints P Zschech, S Weinzierl, N Hambauer, S Zilker, M Kraus (ECIS '22) 30th European Conference on Information Systems, Timisoara, Romania, 2022 | 6 | 2022 |
| Modeling longitudinal dynamics of comorbidities B Maag, S Feuerriegel, M Kraus, M Saar-Tsechansky, T Züger Proceedings of the Conference on Health, Inference, and Learning, 222-235, 2021 | 6 | 2021 |
| White coat adherence effect on glucose control in adult individuals with diabetes T Zueger, M Gloor, V Lehmann, A Melmer, M Kraus, S Feuerriegel, ... Diabetes research and clinical practice 168, 108392, 2020 | 6 | 2020 |
| Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models J Zipfel, F Verworner, M Fischer, U Wieland, M Kraus, P Zschech Computers & Industrial Engineering 177, 109045, 2023 | 4 | 2023 |
