Research

2023

• Kraus M., Tschernutter D., Weinzierl S., Zschech P.:
  Interpretable generalized additive neural networks
  In: European Journal of Operational Research (2023)
  ISSN: 0377-2217
  DOI: 10.1016/j.ejor.2023.06.032
• Schoormann T., Strobel G., Möller F., Petrik D., Zschech P.:
  Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature
  In: Communications of the Association for Information Systems 52 (2023), Article No.: 8
  ISSN: 1529-3181
  DOI: 10.17705/1cais.05209
  URL: https://aisel.aisnet.org/cais/vol52/iss1/8/
• Wanner J., Wissuchek C., Welsch G., Janiesch C.:
  A Taxonomy and Archetypes of Business Analytics in Smart Manufacturing
  In: Data Base for Advances in Information Systems 54 (2023), p. 11-45
  ISSN: 0095-0033
  DOI: 10.1145/3583581.3583584
• Zilker S., Weinzierl S., Zschech P., Kraus M., Matzner M.:
  Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction
  European Conference on Information Systems (Kristiansand, 13. June 2023 - 16. June 2023)
  In: Proceedings of the 31st European Conference on Information Systems 2023
• Zipfel J., Verworner F., Fischer M., Wieland U., Kraus M., Zschech P.:
  Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
  In: Computers & Industrial Engineering 177 (2023), Article No.: 109045
  ISSN: 0360-8352
  DOI: 10.1016/j.cie.2023.109045

2022

• Graf J., Lancho G., Zschech P., Heinrich K.:
  Where Was COVID-19 First Discovered? Designing a Question-Answering System for Pandemic Situations
  European Conference on Information Systems (Timisoara, 18. June 2022 - 24. June 2022)
  In: Proceedings of the 30th European Conference on Information Systems 2022
  URL: https://aisel.aisnet.org/ecis2022_rp/104/
• Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
  A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
  In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
  Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
  URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
• Sager C., Zschech P., Kühl N.:
  labelCloud: A Lightweight Labeling Tool for Domain-Agnostic 3D Object Detection in Point Clouds
  In: Computer-Aided Design and Applications 19 (2022), p. 1191-1206
  ISSN: 1686-4360
  DOI: 10.14733/cadaps.2022.1191-1206
  URL: http://cad-journal.net/files/vol_19/CAD_19(6)_2022_1191-1206.pdf
• Siebers P., Janiesch C., Zschech P.:
  A Survey of Text Representation Methods and Their Genealogy
  In: IEEE Access 10 (2022), p. 96492-96513
  ISSN: 2169-3536
  DOI: 10.1109/ACCESS.2022.3205719
• Zschech P.:
  Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines
  In: Information Systems and E-Business Management (2022)
  ISSN: 1617-9846
  DOI: 10.1007/s10257-022-00577-0
• Zschech P.:
  Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines
  In: Information Systems and E-Business Management (2022)
  ISSN: 1617-9846
  DOI: 10.1007/s10257-022-00577-0
• Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
  GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
  European Conference on Information Systems (Timisoara, 5. July 2022 - 9. July 2022)
  In: Proceedings of the 30th European Conference on Information Systems 2022

2021

• Heinrich K., Zschech P., Janiesch C., Bonin M.:
  Process Data Properties Matter: Introducing Gated Convolutional Neural Networks (GCNN) and Key-Value-Predict Attention Networks (KVP) for Next Event Prediction with Deep Learning
  In: Decision Support Systems (2021), p. 113494
  ISSN: 0167-9236
  DOI: 10.1016/j.dss.2021.113494
  URL: https://www.sciencedirect.com/science/article/pii/S016792362100004X?via=ihub
• Janiesch C., Zschech P., Heinrich K.:
  Machine Learning and Deep Learning
  In: Electronic Markets 31 (2021), p. 685–695
  ISSN: 1019-6781
  DOI: 10.1007/s12525-021-00475-2
  URL: https://link.springer.com/article/10.1007/s12525-021-00475-2
• Petrik D., Pantow K., Zschech P., Herzwurm G.:
  Tweeting in IIoT Ecosystems – Empirical Insights from Social Media Analytics about IIoT Platforms
  16th International Conference on Wirtschaftsinformatik (WI) (Duisburg-Essen, 9. March 2021 - 11. March 2021)
  In: Ahlemann F., Schütte R., Stieglitz S. (ed.): Proceedings of the 16th International Conference on Wirtschaftsinformatik (WI) 2021
  DOI: 10.1007/978-3-030-86800-0_32
  URL: https://aisel.aisnet.org/wi2021/GFuture18/Track18/3/
• Sager C., Janiesch C., Zschech P.:
  A Survey of Image Labelling for Computer Vision Applications
  In: Journal of Business Analytics 4 (2021), p. 91-110
  ISSN: 2573-234X
  DOI: 10.1080/2573234X.2021.1908861
• Sager C., Zschech P., Kühl N.:
  labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds
  International CAD Conference (Barcelona, 5. July 2021 - 7. July 2021)
  In: Proceedings of CAD’21 2021
  DOI: 10.14733/cadconfP.2021.319-323
• Zschech P., Heinrich K., Möller B., Breithaupt L., Maresch J., Roth A.:
  Deep Learning in der Landwirtschaft – Analyse eines Weinbergs
  In: D'Onofrio S., Meier A. (ed.): Big Data Analytics, 2021, p. 169-194
  ISBN: 9783658322359
  DOI: 10.1007/978-3-658-32236-6_8
  URL: https://link.springer.com/chapter/10.1007/978-3-658-32236-6_8
• Zschech P., Sager C., Siebers P., Pertermann M.:
  Mit Computer Vision zur automatisierten Qualitätssicherung in der industriellen Fertigung: Eine Fallstudie zur Klassifizierung von Fehlern in Solarzellen mittels Elektrolumineszenz-Bildern
  In: HMD : Praxis der Wirtschaftsinformatik (2021), p. 321–342
  ISSN: 1436-3011
  DOI: 10.1365/s40702-020-00641-8
  URL: https://link.springer.com/article/10.1365/s40702-020-00641-8
• Zschech P., Walk J., Heinrich K., Vössing M., Kühl N.:
  A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems
  29th European Conference on Information Systems (ECIS) (Virtual Conference, 14. June 2021 - 16. June 2021)
  In: Proceedings of the 29th European Conference on Information Systems (ECIS) 2021
  URL: https://aisel.aisnet.org/ecis2021_rp/127/

2020

• Friederich J., Zschech P.:
  Review and Systematization of Solutions for 3D Object Detection
  15th International Conference on Wirtschaftsinformatik (WI) (Potsdam, 8. March 2020 - 11. March 2020)
  In: Gronau N, Heine M, Krasnova H, Pousttchi K (ed.): Proceedings of the 15th International Conference on Wirtschaftsinformatik, Berlin: 2020
  DOI: 10.30844/wi_2020_r2-friedrich
  URL: https://library.gito.de/oa_wi2020-r2.html
• Heinrich K., Graf J., Chen J., Laurisch J., Zschech P.:
  Fool Me Once, Shame On You, Fool Me Twice, Shame On Me: A Taxonomy of Attack and Defense Patterns for AI Security
  28th European Conference on Information Systems (ECIS) (Virtual Conference, 15. June 2020 - 17. June 2020)
  In: Association for Information Systems (ed.): Proceedings of the 28th European Conference on Information Systems 2020
  URL: https://aisel.aisnet.org/ecis2020_rp/166/
• Heinrich K., Zschech P., Janiesch C., Bonin M.:
  Ein Vergleich aktueller Deep-Learning-Architekturen zur Prognose von Prozessverhalten
  15th International Conference on Wirtschaftsinformatik (WI) (Potsdam, 8. March 2020 - 11. March 2020)
  In: Gronau N, Heine M, Krasnova H, Pousttchi K (ed.): Proceedings of the 15th International Conference on Wirtschaftsinformatik, Berlin: 2020
  DOI: 10.30844/wi_2020_i1-heinrich
  URL: https://library.gito.de/oa_wi2020-i1.html
• Wanner J., Heinrich K., Janiesch C., Zschech P.:
  How Much AI Do You Require? Decision Factors for Adopting AI Technology
  41st International Conference on Information Systems (ICIS) (Virtual Conference, 13. December 2020 - 16. December 2020)
  In: Association for Information Systems (ed.): Proceedings of the 41st International Conference on Information Systems 2020
  URL: https://aisel.aisnet.org/icis2020/implement_adopt/implement_adopt/10/
• Wanner J., Herm LV., Heinrich K., Janiesch C., Zschech P.:
  White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems
  40th International Conference on Information Systems (ICIS) (Virtual Conference, 13. December 2020 - 16. December 2020)
  In: Association for Information Systems (ed.): Proceedings of the 40th International Conference on Information Systems 2020
  URL: https://aisel.aisnet.org/icis2020/hci_artintel/hci_artintel/14/
• Zschech P.:
  Data Science and Analytics in Industrial Maintenance: Selection, Evaluation, and Application of Data-Driven Methods (Dissertation, 2020)
  URL: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-723182
• Zschech P., Horn R., Hoeschele D., Janiesch C., Heinrich K.:
  Intelligent User Assistance for Automated Data Mining Method Selection
  In: Business & Information Systems Engineering 62 (2020), p. 227-247
  ISSN: 1867-0202
  DOI: 10.1007/s12599-020-00642-3
  URL: https://link.springer.com/article/10.1007/s12599-020-00642-3

2019

• Heinrich K., Möller B., Janiesch C., Zschech P.:
  Is Bigger Always Better? Lessons Learnt from the Evolution of Deep Learning Architectures for Image Classification
  Pre-ICIS SIGDSA Symposium (Munich, 14. December 2019 - 15. December 2019)
  In: Proceedings of the Pre-ICIS SIGDSA Symposium 2019
  URL: https://aisel.aisnet.org/sigdsa2019/20/
• Heinrich K., Roth A., Zschech P.:
  Everything Counts: A Taxonomy of Deep Learning Approaches for Object Counting
  27th European Conference on Information Systems (ECIS) (Stockholm & Uppsala, 8. June 2019 - 14. June 2019)
  In: Proceedings of the 27th European Conference on Information Systems 2019
  URL: https://aisel.aisnet.org/ecis2019_rp/63/
• Heinrich K., Zschech P., Möller B., Breithaupt L., Maresch J.:
  Objekterkennung im Weinanbau – Eine Fallstudie zur Unterstützung von Winzertätigkeiten mithilfe von Deep Learning
  In: HMD : Praxis der Wirtschaftsinformatik 56 (2019), p. 964-985
  ISSN: 1436-3011
  DOI: 10.1365/s40702-019-00514-9
  URL: https://link.springer.com/article/10.1365/s40702-019-00514-9
• Heinrich K., Zschech P., Skouti T., Griebenow J., Riechert S.:
  Demystifying the Black Box: A Classification Scheme for Interpretation and Visualization of Deep Intelligent Systems
  25th Americas Conference on Information Systems (AMCIS) (Cancún, 15. August 2019 - 17. August 2019)
  In: Proceedings of the 25th Americas Conference on Information Systems 2019
  URL: https://aisel.aisnet.org/amcis2019/ai_semantic_for_intelligent_info_systems/ai_semantic_for_intelligent_info_systems/8/
• Horn R., Zschech P.:
  Application of Process Mining Techniques to Support Maintenance-Related Objectives
  14th International Conference on Wirtschaftsinformatik (WI) (Siegen, 23. February 2019 - 27. February 2019)
  In: Ludwig T, Pipek V (ed.): Proceedings of the 14th International Conference on Wirtschaftsinformatik, Siegen: 2019
  DOI: 10.25819/ubsi/1016
  URL: https://aisel.aisnet.org/wi2019/specialtrack01/papers/6/
• Zschech P., Bernien J., Heinrich K.:
  Towards a Taxonomic Benchmarking Framework for Predictive Maintenance: The Case of NASA’s Turbofan Degradation
  40th International Conference on Information Systems (ICIS) (München, 15. December 2019 - 18. December 2019)
  In: Proceedings of the 40th International Conference on Information Systems 2019
  URL: https://aisel.aisnet.org/icis2019/data_science/data_science/4/
• Zschech P., Heinrich K., Bink R., Neufeld JS.:
  Prognostic Model Development with Missing Labels: A Condition-Based Maintenance Approach Using Machine Learning
  In: Business & Information Systems Engineering 61 (2019), p. 327-343
  ISSN: 1867-0202
  DOI: 10.1007/s12599-019-00596-1
  URL: https://link.springer.com/article/10.1007/s12599-019-00596-1
• Zschech P., Heinrich K., Horn R., Hoeschele D.:
  Towards a Text-based Recommender System for Data Mining Method Selection
  25th Americas Conference on Information Systems (AMCIS) (Cancún, 15. August 2019 - 17. August 2019)
  In: Proceedings of the 25th Americas Conference on Information Systems 2019
  URL: https://aisel.aisnet.org/amcis2019/ai_semantic_for_intelligent_info_systems/ai_semantic_for_intelligent_info_systems/4/

2018

• Bink R., Zschech P.:
  Predictive Maintenance in der industriellen Praxis: Entwicklung eines Prognoseansatzes unter eingeschränkter Informationslage
  In: HMD : Praxis der Wirtschaftsinformatik 55 (2018), p. 552-565
  ISSN: 1436-3011
  DOI: 10.1365/s40702-017-0378-2
  URL: https://link.springer.com/article/10.1365/s40702-017-0378-2
• Könning M., Heinrich K., Zschech P., Leyh C.:
  Analyzing Influences on Pivotal ITO Contract Features: A Quantitative Multi-Study Design with Evidence from Western Europe
  24th Americas Conference on Information Systems (AMCIS) (New Orleans, 16. August 2018 - 18. August 2018)
  In: Proceedings of the 24th Americas Conference on Information Systems 2018
  URL: https://aisel.aisnet.org/amcis2018/OrgTrasfm/Presentations/17/
• Stefani K., Zschech P.:
  Constituent Elements for Prescriptive Analytics Systems
  26th European Conference on Information Systems (ECIS) (Portsmouth, 23. June 2018 - 28. June 2018)
  In: Proceedings of the 26th European Conference on Information Systems 2018
  URL: https://aisel.aisnet.org/ecis2018_rp/39/
• Zschech P.:
  A Taxonomy of Recurring Data Analysis Problems in Maintenance Analytics
  26th European Conference on Information Systems (ECIS) (Portsmouth, 23. June 2018 - 28. June 2018)
  In: Proceedings of the 26th European Conference on Information Systems 2018
  URL: https://aisel.aisnet.org/ecis2018_rp/197/
• Zschech P., Fleißner V., Baumgärtel N., Hilbert A.:
  Data Science Skills and Enabling Enterprise Systems: Eine Erhebung von Kompetenzanforderungen und Weiterbildungsangeboten
  In: HMD : Praxis der Wirtschaftsinformatik 55 (2018), p. 163-181
  ISSN: 1436-3011
  DOI: 10.1365/s40702-017-0376-4
  URL: https://link.springer.com/article/10.1365/s40702-017-0376-4

2017

• Zschech P., Heinrich K., Pfitzner M., Hilbert A.:
  Are You Up for the Challenge? Towards the Development of a Big Data Capability Assessment Model
  25th European Conference on Information Systems (ECIS) (Guimarães, 5. June 2017 - 10. June 2017)
  In: Proceedings of the 25th European Conference on Information Systems 2017
  URL: https://aisel.aisnet.org/ecis2017_rip/14/
• Zschech P., Pfitzner M., Hilbert A.:
  Vom Controller zum Prozessanalysten
  In: Controlling & Management Review 61 (2017), p. 24-33
  ISSN: 2195-8262
  DOI: 10.1007/s12176-017-0031-5

2016

• Hilbert A., Zschech P.:
  Process Analytics
  In: Das Wirtschaftsstudium 45 (2016), p. 942 - 948
  ISSN: 0340-3084
• Schumann C., Zschech P., Hilbert A.:
  Das aufstrebende Berufsbild des Data Scientist: Vom Kompetenzwirrwarr zu spezifischen Anforderungsprofilen
  In: HMD : Praxis der Wirtschaftsinformatik 53 (2016), p. 453-466
  ISSN: 1436-3011
  DOI: 10.1365/s40702-016-0214-0
  URL: https://link.springer.com/article/10.1365/s40702-016-0214-0

2014

• Kruse P., Kummer C., Zschech P.:
  Existieren Wissensmanagement-Schulen? Eine Clusteranalyse von Wissensmanagement-Beiträgen aus den letzten 10 Jahren
  17. Workshop Gemeinschaften in Neuen Medien: Virtual Enterprises, Research Communities and Social Media Networks - Online Communities: Technologies and Analyses for Networks in Industry, Research and Education, (GeNeMe) (Dresden, 1. October 2014 - 2. October 2014)
  Open Access: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa-154012
  URL: https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa-154012

2023

• Kraus M., Tschernutter D., Weinzierl S., Zschech P.:
  Interpretable generalized additive neural networks
  In: European Journal of Operational Research (2023)
  ISSN: 0377-2217
  DOI: 10.1016/j.ejor.2023.06.032
• Lehmann V., Foll S., Maritsch M., van Weenen E., Kraus M., Lagger S., Odermatt K., Albrecht C., Fleisch E., Zueger T., Wortmann F., Stettler C.:
  Noninvasive Hypoglycemia Detection in People With Diabetes Using Smartwatch Data
  In: Diabetes Care 46 (2023), p. 993-997
  ISSN: 0149-5992
  DOI: 10.2337/dc22-2290
• Lehmann V., Zueger T., Maritsch M., Kraus M., Albrecht C., Berube C., Feuerriegel S., Wortmann F., Kowatsch T., Styger N., Lagger S., Laimer M., Fleisch E., Stettler C.:
  Machine learning for non-invasive sensing of hypoglycaemia while driving in people with diabetes
  In: Diabetes Obesity & Metabolism (2023)
  ISSN: 1462-8902
  DOI: 10.1111/dom.15021
• Schallmoser S., Zueger T., Kraus M., Saar-Tsechansky M., Stettler C., Feuerriegel S.:
  Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study
  In: Journal of Medical Internet Research 25 (2023), p. e42181-
  ISSN: 1438-8871
  DOI: 10.2196/42181
• Stammbach D., Webersinke N., Bingler JA., Kraus M., Leippold M.:
  Environmental Claim Detection
  61st Annual Meeting of the Association for Computational Linguistics (Toronto, 9. July 2023 - 14. July 2023)
  In: Association for Computational Linguistics (ed.): Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) 2023
  Open Access: https://aclanthology.org/2023.acl-short.91
  URL: https://aclanthology.org/2023.acl-short.91
• Zilker S., Weinzierl S., Zschech P., Kraus M., Matzner M.:
  Best of both worlds: Combining predictive power with interpretable and explainable results for patient pathway prediction
  European Conference on Information Systems (Kristiansand, 13. June 2023 - 16. June 2023)
  In: Proceedings of the 31st European Conference on Information Systems 2023
• Zipfel J., Verworner F., Fischer M., Wieland U., Kraus M., Zschech P.:
  Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
  In: Computers & Industrial Engineering 177 (2023), Article No.: 109045
  ISSN: 0360-8352
  DOI: 10.1016/j.cie.2023.109045

2022

• Bingler JA., Kraus M., Leippold M., Webersinke N.:
  Cheap Talk and Cherry-Picking: What ClimateBert has to say on Corporate Climate Risk Disclosures
  In: Finance Research Letters 47 (2022), p. 102776
  ISSN: 1544-6123
  DOI: 10.1016/j.frl.2022.102776
• Bingler JA., Kraus M., Leippold M., Webersinke N.:
  Cheap Talk in Corporate Climate Commitments: The effectiveness of climate initiatives
  In: Social Science Research Network (2022)
  DOI: 10.2139/ssrn.3998435
  (Working Paper)
• Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
  A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
  In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
  Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
  URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
• Hershcovich D., Webersinke N., Kraus M., Bingler JA., Leippold M.:
  Towards Climate Awareness in NLP Research
  EMNLP 2022: The 2022 Conference on Empirical Methods in Natural Language Processing (Abu Dhabi, 7. December 2022 - 11. December 2022)
  In: Association for Computational Linguistics (ed.): Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing 2022
  Open Access: https://aclanthology.org/2022.emnlp-main.159
  URL: https://aclanthology.org/2022.emnlp-main.159
• Lorenz R., Kraus M., Wolf H., Feuerriegel S., Netland TH.:
  Selecting advanced analytics in manufacturing: a decision support model
  In: Production Planning & Control (2022)
  ISSN: 0953-7287
  DOI: 10.1080/09537287.2022.2126951
• Webersinke N., Kraus M., Bingler JA., Leippold M.:
  ClimateBert: A Pretrained Language Model for Climate-Related Text
  AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges (Arlington, VA, 17. November 2022 - 19. November 2022)
  In: Proceedings of AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges 2022
  DOI: 10.2139/ssrn.4229146
  URL: https://www.climatechange.ai/papers/aaaifss2022/12
• Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
  GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
  European Conference on Information Systems (Timisoara, 5. July 2022 - 9. July 2022)
  In: Proceedings of the 30th European Conference on Information Systems 2022
• Zueger T., Schallmoser S., Kraus M., Saar-Tsechansky M., Feuerriegel S., Stettler C.:
  Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes
  In: Diabetes Technology & Therapeutics (2022)
  ISSN: 1520-9156
  DOI: 10.1089/dia.2022.0210

2021

• Bingler JA., Kraus M., Leippold M.:
  Cheap Talk and Cherry-Picking: What ClimateBert has to say on Corporate Climate Risk Disclosures
  In: Social Science Research Network (2021)
  ISSN: 1556-5068
  DOI: 10.2139/ssrn.3796152
• Maag B., Feuerriegel S., Kraus M., Saar-Tsechansky M., Züger T.:
  Modeling longitudinal dynamics of comorbidities
  2021 ACM Conference on Health, Inference, and Learning, CHIL 2021 (, 8. April 2021 - 9. April 2021)
  In: ACM CHIL 2021 - Proceedings of the 2021 ACM Conference on Health, Inference, and Learning 2021
  DOI: 10.1145/3450439.3451871
• Ozyurt Y., Kraus M., Hatt T., Feuerriegel S.:
  AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
  27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021 (Virtual, 14. August 2021 - 18. August 2021)
  In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2021
  DOI: 10.1145/3447548.3467143
• la Torre AMD., van Weenen E., Kraus M., Weiler S., Feuerriegel S., Burden AM.:
  A network analysis of drug combinations associated with acute generalized exanthematous pustulosis (AGEP)
  In: Journal of Clinical Medicine 10 (2021), Article No.: 4486
  ISSN: 2077-0383
  DOI: 10.3390/jcm10194486

2020

• Ducci F., Kraus M., Feuerriegel S.:
  Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades
  26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2020 (, 23. August 2020 - 27. August 2020)
  In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2020
  DOI: 10.1145/3394486.3403317
• Kraus M., Feuerriegel S., Oztekin A.:
  Deep learning in business analytics and operations research: Models, applications and managerial implications
  In: European Journal of Operational Research 281 (2020), p. 628-641
  ISSN: 0377-2217
  DOI: 10.1016/j.ejor.2019.09.018
• Maritsch M., Föll S., Lehmann V., Bérubé C., Kraus M., Feuerriegel S., Kowatsch T., Züger T., Stettler C., Fleisch E., Wortmann F.:
  Towards wearable-based hypoglycemia detection and warning in diabetes
  2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 (Honolulu, HI, 25. April 2020 - 30. April 2020)
  In: Conference on Human Factors in Computing Systems - Proceedings 2020
  DOI: 10.1145/3334480.3382808
• Zueger T., Gloor M., Lehmann V., Melmer A., Kraus M., Feuerriegel S., Laimer M., Stettler C.:
  White coat adherence effect on glucose control in adult individuals with diabetes
  In: Diabetes Research and Clinical Practice 168 (2020), Article No.: 108392
  ISSN: 0168-8227
  DOI: 10.1016/j.diabres.2020.108392

2019

• Kraus M., Feuerriegel S.:
  Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
  In: Decision Support Systems 125 (2019), Article No.: 113100
  ISSN: 0167-9236
  DOI: 10.1016/j.dss.2019.113100
• Kraus M., Feuerriegel S.:
  Personalized purchase prediction of market baskets with Wasserstein-based sequence matching
  25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019 (Anchorage, AK, 4. August 2019 - 8. August 2019)
  In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2019
  DOI: 10.1145/3292500.3330791
• Kraus M., Feuerriegel S.:
  Sentiment analysis based on rhetorical structure theory:Learning deep neural networks from discourse trees
  In: Expert Systems With Applications 118 (2019), p. 65-79
  ISSN: 0957-4174
  DOI: 10.1016/j.eswa.2018.10.002
• Maritsch M., Berube C., Kraus M., Lehmann V., Zuger T., Feuerriegel S., Kowatsch T., Wortmann F.:
  Improving heart rate variability measurements from consumer smartwatches with machine learning
  2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2019 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2019 (London, 9. September 2019 - 13. September 2019)
  In: UbiComp/ISWC 2019- - Adjunct 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
  DOI: 10.1145/3341162.3346276
• Wolf H., Lorenz R., Kraus M., Feuerriegel S., Netland TH.:
  Bringing Advanced Analytics to Manufacturing: A Systematic Mapping
  IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2019 (Austin, TX, 1. September 2019 - 5. September 2019)
  In: Farhad Ameri, Kathryn E. Stecke, Gregor von Cieminski, Dimitris Kiritsis (ed.): IFIP Advances in Information and Communication Technology 2019
  DOI: 10.1007/978-3-030-30000-5_42

2018

• Kratzwald B., Ilic S., Kraus M., Feuerriegel S., Prendinger H.:
  Deep learning for affective computing: Text-based emotion recognition in decision support
  In: Decision Support Systems 115 (2018), p. 24-35
  ISSN: 0167-9236
  DOI: 10.1016/j.dss.2018.09.002

2017

• Kraus M., Feuerriegel S.:
  Decision support from financial disclosures with deep neural networks and transfer learning
  In: Decision Support Systems 104 (2017), p. 38-48
  ISSN: 0167-9236
  DOI: 10.1016/j.dss.2017.10.001

2022

• Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
  A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
  In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
  Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
  URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
• Zschech P., Weinzierl S., Hambauer N., Zilker S., Kraus M.:
  GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
  European Conference on Information Systems (Timisoara, 5. July 2022 - 9. July 2022)
  In: Proceedings of the 30th European Conference on Information Systems 2022

2022

• Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
  A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
  In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
  Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
  URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/