Mathias Kraus

73 papers A* 6C 1Journal 47Unranked 18
YearRankTypeTitle / Venue / Authors
2026 J jnl
Challenging the Performance-Interpretability Trade-Off: An Evaluation of Interpretable Machine Learning Models.
Bus. Inf. Syst. Eng.
Sven Kruschel, Nico Hambauer, Sven Weinzierl, Sandra Zilker, Mathias Kraus, Patrick Zschech
2026 J jnl
Inherently Interpretable Machine Learning: A Contrasting Paradigm to Post-hoc Explainable AI.
Bus. Inf. Syst. Eng.
Patrick Zschech, Sven Weinzierl, Mathias Kraus
2025 J jnl
Analyzing German Parliamentary Speeches: A Machine Learning Approach for Topic and Sentiment Classification.
CoRR
Lukas Pätz, Moritz Beyer, Jannik Späth, Lasse Bohlen, Patrick Zschech, Mathias Kraus, Julian Rosenberger
2025 — conf
Benchmarking Cluster-Then-Predict Models to Challenge Prevailing Global Machine Learning Models.
HICSS
Nico Hambauer, Theodor Stoecker, Patrick Zschech, Mathias Kraus
2025 J jnl
Beware of "Explanations" of AI.
CoRR
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
2025 J jnl
CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendations.
CoRR
Julian Rosenberger, Lukas Wolfrum, Sven Weinzierl, Mathias Kraus, Patrick Zschech
2025 J jnl
CareerBERT: Matching resumes to ESCO jobs in a shared embedding space for generic job recommendations.
Expert Syst. Appl.
Julian Rosenberger, Lukas Wolfrum, Sven Weinzierl, Mathias Kraus, Patrick Zschech
2025 J jnl
Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict.
CoRR
Simon Hofmann, Christoph Sommermann, Mathias Kraus, Patrick Zschech, Julian Rosenberger
2025 — conf
Introduction to the Minitrack on Personal Health Management with Digital Solutions.
HICSS
Nilmini Wickramasinghe, Mathias Kraus, Elliot B. Sloane, Freimut Bodendorf
2025 J jnl
Leveraging interpretable machine learning in intensive care.
Ann. Oper. Res.
Lasse Bohlen, Julian Rosenberger, Patrick Zschech, Mathias Kraus
2025 A* conf
Moving Beyond the Simulator: Interaction-Based Drunk Driving Detection in a Real Vehicle Using Driver Monitoring Cameras and Real-Time Vehicle Data.
CHI
Robin Deuber, Patrick Langer, Mathias Kraus, Matthias Pfäffli, Matthias Bantle, Filipe Barata, Florian von Wangenheim, Elgar Fleisch, Wolfgang Weinmann, Felix Wortmann
2025 — conf
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users.
ECIS
Julian Rosenberger, Philipp Schröppel, Sven Kruschel, Mathias Kraus, Patrick Zschech, Maximilian Förster
2025 J jnl
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users.
CoRR
Julian Rosenberger, Philipp Schröppel, Sven Kruschel, Mathias Kraus, Patrick Zschech, Maximilian Förster
2025 J jnl
Overcoming Algorithm Aversion with Transparency: Can Transparent Predictions Change User Behavior?
CoRR
Lasse Bohlen, Sven Kruschel, Julian Rosenberger, Patrick Zschech, Mathias Kraus
2025 J jnl
The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment.
CoRR
Julian Rosenberger, Sophie Kuhlemann, Verena Tiefenbeck, Mathias Kraus, Patrick Zschech
2025 J jnl
Unveiling Location-Specific Price Drivers: A Two-Stage Cluster Analysis for Interpretable House Price Predictions.
CoRR
Paul Gümmer, Julian Rosenberger, Mathias Kraus, Patrick Zschech, Nico Hambauer
2024 J jnl
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions.
CoRR
Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel
2024 J jnl
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions.
Trans. Mach. Learn. Res.
Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel
2024 J jnl
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis.
CoRR
Sandra Zilker, Sven Weinzierl, Mathias Kraus, Patrick Zschech, Martin Matzner
2024 J jnl
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models.
CoRR
Sven Kruschel, Nico Hambauer, Sven Weinzierl, Sandra Zilker, Mathias Kraus, Patrick Zschech
2024 — conf
Coupling Neural Networks Between Clusters for Better Personalized Care.
HICSS
Mathias Kraus, Nico Hambauer, Kristina Müller, Pavlina Kröckel, Nalika Ulapane, Arno De Caigny, Koen W. De Bock, Kristof Coussement
2024 J jnl
Data-Driven Allocation of Preventive Care with Application to Diabetes Mellitus Type II.
Manuf. Serv. Oper. Manag.
Mathias Kraus, Stefan Feuerriegel, Maytal Saar-Tsechansky
2024 J jnl
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda.
Eur. J. Oper. Res.
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
2024 J jnl
Explainable AI for enhanced decision-making.
Decis. Support Syst.
Kristof Coussement, Mohammad Zoynul Abedin, Mathias Kraus, Sebastián Maldonado, Kazim Topuz
2024 — conf
Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict.
Wirtschaftsinformatik
Simon Hofmann, Christoph Sommermann, Mathias Kraus, Patrick Zschech, Julian Rosenberger
2024 C conf
How Risky is my AI System? A Method for Transparent Classification of AI System Descriptions by Regulated AI Risk Categories.
ICIS
Sven Weinzierl, Sandra Zilker, Patrick Zschech, Mathias Kraus, Tobias Leibelt, Martin Matzner
2024 — conf
IGANN Sparse: Bridging Sparsity and Interpretability with Non-Linear Insight.
ECIS
Theodor Felix Stoecker, Nico Hambauer, Patrick Zschech, Mathias Kraus
2024 J jnl
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight.
CoRR
Theodor Stoecker, Nico Hambauer, Patrick Zschech, Mathias Kraus
2024 J jnl
Interpretable generalized additive neural networks.
Eur. J. Oper. Res.
Mathias Kraus, Daniel Tschernutter, Sven Weinzierl, Patrick Zschech
2024 J jnl
Quantifying Visual Properties of GAM Shape Plots: Impact on Perceived Cognitive Load and Interpretability.
CoRR
Sven Kruschel, Lasse Bohlen, Julian Rosenberger, Patrick Zschech, Mathias Kraus
2024 — conf
The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment.
Wirtschaftsinformatik
Julian Rosenberger, Sophie Kuhlemann, Verena Tiefenbeck, Mathias Kraus, Patrick Zschech
2024 — conf
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering.
ACL (1)
Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, Markus Leippold
2024 J jnl
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering.
CoRR
Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, Markus Leippold
2023 — conf
A Suggested Blockchain Architecture for Healthcare Data Sharing.
AMCIS
Nilmini Wickramasinghe, Nalika Ulapane, Amirhossein Eslami Andargoli, Jan Miltner, Jule van de Logt, Mathias Kraus, Freimut Bodendorf
2023 J jnl
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models.
Comput. Ind. Eng.
Justus Zipfel, Felix Verworner, Marco Fischer, Uwe Wieland, Mathias Kraus, Patrick Zschech
2023 — conf
Best of Both Worlds: Combining Predictive Power with Interpretable and Explainable Results for Patient Pathway Prediction.
ECIS
Sandra Zilker, Sven Weinzierl, Patrick Zschech, Mathias Kraus, Martin Matzner
2023 — conf
CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools.
EMNLP (Demos)
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
2023 J jnl
CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools.
CoRR
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
2023 A* conf
ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets.
EMNLP
Tobias Schimanski, Julia Anna Bingler, Mathias Kraus, Camilla Hyslop, Markus Leippold
2023 J jnl
ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets.
CoRR
Tobias Schimanski, Julia Anna Bingler, Camilla Hyslop, Mathias Kraus, Markus Leippold
2023 J jnl
Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type II.
CoRR
Mathias Kraus, Stefan Feuerriegel, Maytal Saar-Tsechansky
2023 J jnl
Enhancing Large Language Models with Climate Resources.
CoRR
Mathias Kraus, Julia Anna Bingler, Markus Leippold, Tobias Schimanski, Chiara Colesanti Senni, Dominik Stammbach, Saeid Ashraf Vaghefi, Nicolas Webersinke
2023 — conf
Environmental Claim Detection.
ACL (2)
Dominik Stammbach, Nicolas Webersinke, Julia Anna Bingler, Mathias Kraus, Markus Leippold
2023 J jnl
chatClimate: Grounding Conversational AI in Climate Science.
CoRR
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
2022 J jnl
A Dataset for Detecting Real-World Environmental Claims.
CoRR
Dominik Stammbach, Nicolas Webersinke, Julia Anna Bingler, Mathias Kraus, Markus Leippold
2022 — conf
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision.
Wirtschaftsinformatik
Maximilian V. Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer, Patrick Zschech, Mathias Kraus
2022 J jnl
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision.
CoRR
Maximilian Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer, Patrick Zschech, Mathias Kraus
2022 — conf
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints.
ECIS
Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus
2022 J jnl
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints.
CoRR
Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus
2022 A* conf
Towards Climate Awareness in NLP Research.
EMNLP
Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold
2022 J jnl
Towards Climate Awareness in NLP Research.
CoRR
Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold
2021 A* conf
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units.
KDD
Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel
2021 J jnl
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units.
CoRR
Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel
2021 J jnl
ClimateBert: A Pretrained Language Model for Climate-Related Text.
CoRR
Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold
2021 — conf
Modeling longitudinal dynamics of comorbidities.
CHIL
Basil Maag, Stefan Feuerriegel, Mathias Kraus, Maytal Saar-Tsechansky, Thomas Züger
2020 A* conf
Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades.
KDD
Francesco Ducci, Mathias Kraus, Stefan Feuerriegel
2020 — —
Deep Learning in Business Analytics: Methods and Applications.
Mathias Kraus
2020 J jnl
Deep learning in business analytics and operations research: Models, applications and managerial implications.
Eur. J. Oper. Res.
Mathias Kraus, Stefan Feuerriegel, Asil Oztekin
2020 — conf
Towards Wearable-based Hypoglycemia Detection and Warning in Diabetes.
CHI Extended Abstracts
Martin Maritsch, Simon Föll, Vera Lehmann, Caterina Bérubé, Mathias Kraus, Stefan Feuerriegel, Tobias Kowatsch, Thomas Züger, Christoph Stettler, Elgar Fleisch, Felix Wortmann
2019 — conf
Bringing Advanced Analytics to Manufacturing: A Systematic Mapping.
APMS (1)
Hergen Wolf, Rafael Lorenz, Mathias Kraus, Stefan Feuerriegel, Torbjørn H. Netland
2019 J jnl
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences.
CoRR
Mathias Kraus, Stefan Feuerriegel
2019 J jnl
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences.
Decis. Support Syst.
Mathias Kraus, Stefan Feuerriegel
2019 J jnl
Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning.
CoRR
Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann
2019 — conf
Improving heart rate variability measurements from consumer smartwatches with machine learning.
UbiComp/ISWC Adjunct
Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann
2019 A* conf
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching.
KDD
Mathias Kraus, Stefan Feuerriegel
2019 J jnl
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching.
CoRR
Mathias Kraus, Stefan Feuerriegel
2019 J jnl
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees.
Expert Syst. Appl.
Mathias Kraus, Stefan Feuerriegel
2018 J jnl
Decision support with text-based emotion recognition: Deep learning for affective computing.
CoRR
Bernhard Kratzwald, Suzana Ilic, Mathias Kraus, Stefan Feuerriegel, Helmut Prendinger
2018 J jnl
Deep learning for affective computing: Text-based emotion recognition in decision support.
Decis. Support Syst.
Bernhard Kratzwald, Suzana Ilic, Mathias Kraus, Stefan Feuerriegel, Helmut Prendinger
2018 J jnl
Deep learning in business analytics and operations research: Models, applications and managerial implications.
CoRR
Mathias Kraus, Stefan Feuerriegel, Asil Oztekin
2017 J jnl
Decision support from financial disclosures with deep neural networks and transfer learning.
CoRR
Mathias Kraus, Stefan Feuerriegel
2017 J jnl
Decision support from financial disclosures with deep neural networks and transfer learning.
Decis. Support Syst.
Mathias Kraus, Stefan Feuerriegel
2017 J jnl
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees.
CoRR
Mathias Kraus, Stefan Feuerriegel