Mathias Kraus
Orcid: 0000-0002-2021-2743Affiliations:
- University of Erlangen-Nuremberg, Nuremberg, Germany
According to our database1,
Mathias Kraus
authored at least 32 papers
between 2017 and 2024.
Collaborative distances:
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Bibliography
2024
Data-Driven Allocation of Preventive Care with Application to Diabetes Mellitus Type II.
Manuf. Serv. Oper. Manag., January, 2024
CoRR, 2024
CoRR, 2024
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions.
CoRR, 2024
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024
2023
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models.
Comput. Ind. Eng., March, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction.
Proceedings of the 31st European Conference on Information Systems, 2023
Proceedings of the 29th Americas Conference on Information Systems, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023
2022
Proceedings of the WI for Grand Challenges, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints.
Proceedings of the 30th European Conference on Information Systems, 2022
2021
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021
2020
Deep learning in business analytics and operations research: Models, applications and managerial implications.
Eur. J. Oper. Res., 2020
Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020
2019
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees.
Expert Syst. Appl., 2019
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences.
Decis. Support Syst., 2019
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Proceedings of the Advances in Production Management Systems. Production Management for the Factory of the Future, 2019
Improving heart rate variability measurements from consumer smartwatches with machine learning.
Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019
2018
Deep learning for affective computing: Text-based emotion recognition in decision support.
Decis. Support Syst., 2018
Decision support with text-based emotion recognition: Deep learning for affective computing.
CoRR, 2018
2017
Decision support from financial disclosures with deep neural networks and transfer learning.
Decis. Support Syst., 2017