default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMathias Kraus
Person information
- affiliation: University of Erlangen-Nuremberg, Nuremberg, Germany
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 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) - [c17]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 - [c16]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 - [i22]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) - [i21]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) - [i20]Theodor Stoecker, Nico Hambauer, Patrick Zschech, Mathias Kraus:
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight. CoRR abs/2403.11363 (2024) - [i19]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) - 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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-27 22:01 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
