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ORCIDMathias Kraus
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- affiliation: University of Erlangen-Nuremberg, Nuremberg, Germany
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2020 – today
- 2025
[j12]Julian Rosenberger
, Lukas Wolfrum, Sven Weinzierl, Mathias Kraus, Patrick Zschech:
CareerBERT: Matching resumes to ESCO jobs in a shared embedding space for generic job recommendations. Expert Syst. Appl. 275: 127043 (2025)- [c22]Robin Deuber, Patrick Langer, Mathias Kraus, Matthias Pfäffli, Matthias Bantle, Filipe Barata, Florian von Wangenheim, Elgar Fleisch, Wolfgang Weinmann, Felix Wortmann:
Moving Beyond the Simulator: Interaction-Based Drunk Driving Detection in a Real Vehicle Using Driver Monitoring Cameras and Real-Time Vehicle Data. CHI 2025: 84:1-84:25 - [i28]Julian Rosenberger, Sophie Kuhlemann, Verena Tiefenbeck, Mathias Kraus, Patrick Zschech:
The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment. CoRR abs/2502.20243 (2025) - [i27]Julian Rosenberger, Lukas Wolfrum, Sven Weinzierl, Mathias Kraus, Patrick Zschech:
CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendations. CoRR abs/2503.02056 (2025) - [i26]Simon Hofmann, Christoph Sommermann, Mathias Kraus, Patrick Zschech, Julian Rosenberger:
Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict. CoRR abs/2503.10648 (2025) - [i25]David Martens, Galit Shmueli, Theodoros Evgeniou, Kevin Bauer, Christian Janiesch, Stefan Feuerriegel, Sebastian Gabel, Sofie Goethals, Travis Greene, Nadja Klein, Mathias Kraus, Niklas Kühl, Claudia Perlich, Wouter Verbeke, Alona Zharova, Patrick Zschech, Foster J. Provost:
Beware of "Explanations" of AI. CoRR abs/2504.06791 (2025) - 2024
- [j11]Kristof Coussement, Mohammad Zoynul Abedin, Mathias Kraus, Sebastián Maldonado, Kazim Topuz:
Explainable AI for enhanced decision-making. Decis. Support Syst. 184: 114276 (2024) - [j10]Koen W. De Bock, Kristof Coussement, Arno De Caigny, Roman Slowinski, Bart Baesens, Robert N. Boute, Tsan-Ming Choi, Dursun Delen, Mathias Kraus, Stefan Lessmann, Sebastián Maldonado, David Martens, María Óskarsdóttir, Carla Vairetti, Wouter Verbeke, Richard Weber:
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. Eur. J. Oper. Res. 317(2): 249-272 (2024) - [j9]Mathias Kraus, Daniel Tschernutter, Sven Weinzierl, Patrick Zschech:
Interpretable generalized additive neural networks. Eur. J. Oper. Res. 317(2): 303-316 (2024) - [j8]Mathias Kraus, Stefan Feuerriegel, Maytal Saar-Tsechansky:
Data-Driven Allocation of Preventive Care with Application to Diabetes Mellitus Type II. Manuf. Serv. Oper. Manag. 26(1): 137-153 (2024) - [j7]Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel:
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions. Trans. Mach. Learn. Res. 2024 (2024) - [c21]Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, Markus Leippold:
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering. ACL (1) 2024: 1913-1931 - [c20]Theodor Felix Stoecker, Nico Hambauer, Patrick Zschech, Mathias Kraus:
IGANN Sparse: Bridging Sparsity and Interpretability with Non-Linear Insight. ECIS 2024 - [c19]Mathias Kraus, Nico Hambauer, Kristina Müller, Pavlina Kröckel, Nalika Ulapane, Arno De Caigny, Koen W. De Bock, Kristof Coussement:
Coupling Neural Networks Between Clusters for Better Personalized Care. HICSS 2024: 3627-3636 - [c18]Sven Weinzierl, Sandra Zilker, Patrick Zschech, Mathias Kraus, Tobias Leibelt, Martin Matzner:
How Risky is my AI System? A Method for Transparent Classification of AI System Descriptions by Regulated AI Risk Categories. ICIS 2024 - [c17]Julian Rosenberger, Sophie Kuhlemann, Verena Tiefenbeck, Mathias Kraus, Patrick Zschech:
The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment. Wirtschaftsinformatik 2024: 38 - [c16]Simon Hofmann, Christoph Sommermann, Mathias Kraus, Patrick Zschech, Julian Rosenberger:
Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict. Wirtschaftsinformatik 2024: 82 - [i24]Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel:
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions. CoRR abs/2401.07936 (2024) - [i23]Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, Markus Leippold:
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering. CoRR abs/2402.08277 (2024) - [i22]Theodor Stoecker, Nico Hambauer, Patrick Zschech, Mathias Kraus:
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight. CoRR abs/2403.11363 (2024) - [i21]Sandra Zilker, Sven Weinzierl, Mathias Kraus, Patrick Zschech, Martin Matzner:
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis. CoRR abs/2405.13187 (2024) - [i20]Sven Kruschel, Nico Hambauer, Sven Weinzierl, Sandra Zilker, Mathias Kraus, Patrick Zschech:
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models. CoRR abs/2409.14429 (2024) - [i19]Sven Kruschel, Lasse Bohlen, Julian Rosenberger, Patrick Zschech, Mathias Kraus:
Quantifying Visual Properties of GAM Shape Plots: Impact on Perceived Cognitive Load and Interpretability. CoRR abs/2409.16870 (2024) - 2023
- [j6]Justus Zipfel, Felix Verworner, Marco Fischer, Uwe Wieland, Mathias Kraus, Patrick Zschech:
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models. Comput. Ind. Eng. 177: 109045 (2023) - [c15]Dominik Stammbach, Nicolas Webersinke, Julia Anna Bingler, Mathias Kraus, Markus Leippold:
Environmental Claim Detection. ACL (2) 2023: 1051-1066 - [c14]Nilmini Wickramasinghe, Nalika Ulapane, Amirhossein Eslami Andargoli, Jan Miltner, Jule van de Logt, Mathias Kraus, Freimut Bodendorf:
A Suggested Blockchain Architecture for Healthcare Data Sharing. AMCIS 2023 - [c13]Sandra Zilker, Sven Weinzierl, Patrick Zschech, Mathias Kraus, Martin Matzner:
Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction. ECIS 2023 - [c12]Jingwei Ni, Julia Anna Bingler, Chiara Colesanti Senni, Mathias Kraus, Glen Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Ashraf Vaghefi, Qian Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu, Markus Leippold:
CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools. EMNLP (Demos) 2023: 21-51 - [c11]Tobias Schimanski, Julia Anna Bingler, Mathias Kraus, Camilla Hyslop, Markus Leippold:
ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets. EMNLP 2023: 15745-15756 - [i18]Mathias Kraus, Julia Anna Bingler, Markus Leippold, Tobias Schimanski, Chiara Colesanti Senni, Dominik Stammbach, Saeid Ashraf Vaghefi, Nicolas Webersinke:
Enhancing Large Language Models with Climate Resources. CoRR abs/2304.00116 (2023) - [i17]Saeid Ashraf Vaghefi, Qian Wang, Veruska Muccione, Jingwei Ni, Mathias Kraus, Julia Anna Bingler, Tobias Schimanski, Chiara Colesanti Senni, Nicolas Webersinke, Christian Huggel, Markus Leippold:
chatClimate: Grounding Conversational AI in Climate Science. CoRR abs/2304.05510 (2023) - [i16]Jingwei Ni, Julia Anna Bingler, Chiara Colesanti Senni, Mathias Kraus, Glen Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Ashraf Vaghefi, Qian Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu, Markus Leippold:
CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools. CoRR abs/2307.15770 (2023) - [i15]Mathias Kraus, Stefan Feuerriegel, Maytal Saar-Tsechansky:
Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type II. CoRR abs/2308.06959 (2023) - [i14]Tobias Schimanski, Julia Anna Bingler, Camilla Hyslop, Mathias Kraus, Markus Leippold:
ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets. CoRR abs/2310.08096 (2023) - 2022
- [c10]Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints. ECIS 2022 - [c9]Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold:
Towards Climate Awareness in NLP Research. EMNLP 2022: 2480-2494 - [c8]Maximilian V. Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer, Patrick Zschech, Mathias Kraus:
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision. Wirtschaftsinformatik 2022 - [i13]Maximilian Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer, Patrick Zschech, Mathias Kraus:
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision. CoRR abs/2201.02028 (2022) - [i12]Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus:
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints. CoRR abs/2204.09123 (2022) - [i11]Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold:
Towards Climate Awareness in NLP Research. CoRR abs/2205.05071 (2022) - [i10]Dominik Stammbach, Nicolas Webersinke, Julia Anna Bingler, Mathias Kraus, Markus Leippold:
A Dataset for Detecting Real-World Environmental Claims. CoRR abs/2209.00507 (2022) - 2021
- [c7]Basil Maag, Stefan Feuerriegel, Mathias Kraus, Maytal Saar-Tsechansky, Thomas Züger:
Modeling longitudinal dynamics of comorbidities. CHIL 2021: 222-235 - [c6]Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel:
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. KDD 2021: 3452-3462 - [i9]Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel:
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. CoRR abs/2102.04702 (2021) - [i8]Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold:
ClimateBert: A Pretrained Language Model for Climate-Related Text. CoRR abs/2110.12010 (2021) - 2020
- [b1]Mathias Kraus:
Deep Learning in Business Analytics: Methods and Applications. ETH Zurich, Zürich, Switzerland, 2020 - [j5]Mathias Kraus, Stefan Feuerriegel, Asil Oztekin:
Deep learning in business analytics and operations research: Models, applications and managerial implications. Eur. J. Oper. Res. 281(3): 628-641 (2020) - [c5]Martin Maritsch, Simon Föll, Vera Lehmann, Caterina Bérubé, Mathias Kraus, Stefan Feuerriegel, Tobias Kowatsch, Thomas Züger, Christoph Stettler, Elgar Fleisch, Felix Wortmann:
Towards Wearable-based Hypoglycemia Detection and Warning in Diabetes. CHI Extended Abstracts 2020: 1-8 - [c4]Francesco Ducci, Mathias Kraus, Stefan Feuerriegel:
Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades. KDD 2020: 2666-2676
2010 – 2019
- 2019
- [j4]Mathias Kraus, Stefan Feuerriegel:
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences. Decis. Support Syst. 125 (2019) - [j3]Mathias Kraus, Stefan Feuerriegel:
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees. Expert Syst. Appl. 118: 65-79 (2019) - [c3]Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann:
Improving heart rate variability measurements from consumer smartwatches with machine learning. UbiComp/ISWC Adjunct 2019: 934-938 - [c2]Hergen Wolf, Rafael Lorenz, Mathias Kraus, Stefan Feuerriegel, Torbjørn H. Netland:
Bringing Advanced Analytics to Manufacturing: A Systematic Mapping. APMS (1) 2019: 333-340 - [c1]Mathias Kraus, Stefan Feuerriegel:
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching. KDD 2019: 2643-2652 - [i7]Mathias Kraus, Stefan Feuerriegel:
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching. CoRR abs/1905.13131 (2019) - [i6]Mathias Kraus, Stefan Feuerriegel:
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences. CoRR abs/1907.05146 (2019) - [i5]Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann:
Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning. CoRR abs/1907.07496 (2019) - 2018
- [j2]Bernhard Kratzwald, Suzana Ilic, Mathias Kraus, Stefan Feuerriegel, Helmut Prendinger:
Deep learning for affective computing: Text-based emotion recognition in decision support. Decis. Support Syst. 115: 24-35 (2018) - [i4]Bernhard Kratzwald, Suzana Ilic, Mathias Kraus, Stefan Feuerriegel, Helmut Prendinger:
Decision support with text-based emotion recognition: Deep learning for affective computing. CoRR abs/1803.06397 (2018) - [i3]Mathias Kraus, Stefan Feuerriegel, Asil Oztekin:
Deep learning in business analytics and operations research: Models, applications and managerial implications. CoRR abs/1806.10897 (2018) - 2017
- [j1]Mathias Kraus, Stefan Feuerriegel:
Decision support from financial disclosures with deep neural networks and transfer learning. Decis. Support Syst. 104: 38-48 (2017) - [i2]Mathias Kraus, Stefan Feuerriegel:
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees. CoRR abs/1704.05228 (2017) - [i1]Mathias Kraus, Stefan Feuerriegel:
Decision support from financial disclosures with deep neural networks and transfer learning. CoRR abs/1710.03954 (2017)
Coauthor Index
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