Niklas Kühl
Cited by
Cited by
Machine learning operations (MLOps): Overview, definition, and architecture
D Kreuzberger, N Kühl, S Hirschl
IEEE Access, 2023
Machine Learning in Artificial Intelligence: Towards a Common Understanding
N Kühl, M Goutier, R Hirt, G Satzger
Hawaii International Conference on System Sciences (HICSS-52), 2019
Virtual sensors
D Martin, N Kühl, G Satzger
Business & Information Systems Engineering 63, 315-323, 2021
Human-AI Complementarity in Hybrid Intelligence Systems: A Structured Literature Review.
P Hemmer, M Schemmer, M Vössing, N Kühl
PACIS, 78, 2021
Supporting customer-oriented marketing with artificial intelligence: automatically quantifying customer needs from social media
N Kühl, M Mühlthaler, M Goutier
Electronic Markets 30 (2), 351-367, 2020
AI-based resource allocation: Reinforcement learning for adaptive auto-scaling in serverless environments
L Schuler, S Jamil, N Kühl
2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet …, 2021
Artificial intelligence and machine learning
N Kühl, M Schemmer, M Goutier, G Satzger
Electronic Markets 32 (4), 2235-2244, 2022
Deal: Deep evidential active learning for image classification
P Hemmer, N Kühl, J Schöffer
Deep Learning Applications, Volume 3, 171-192, 2022
Literature vs. Twitter: Empirical insights on customer needs in e-mobility
N Kühl, M Goutier, A Ensslen, P Jochem
Journal of cleaner production 213, 508-520, 2019
Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making
M Schemmer, P Hemmer, N Kühl, C Benz, G Satzger
Thirtieth European Conference on Information Systems (ECIS 2022), 2022
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making
J Schoeffer, N Kuehl, Y Machowski
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2022, 2022
How to conduct rigorous supervised machine learning in information systems research: the supervised machine learning report card
N Kühl, R Hirt, L Baier, B Schmitz, G Satzger
Communications of the Association for Information Systems 48 (1), 46, 2021
Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations
M Schemmer, N Kühl, C Benz, A Bartos, G Satzger
🏆 ACM Conference on Intelligent User Interfaces (ACM IUI), 2023
Human vs. supervised machine learning: Who learns patterns faster?
N Kühl, M Goutier, L Baier, C Wolff, D Martin
Cognitive Systems Research, 2022
A Meta-Analysis on the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making
M Schemmer, P Hemmer, M Nitsche, N Kühl, M Vössing
AAAI /ACM Conference on Artificial Intelligence, Ethics and Society (AIES) 2022, 2022
Needmining: Identifying Micro Blog Data Containing Customer Needs
N Kuehl, J Scheurenbrand, G Satzger
Proceedings of the 24th European Conference of Information Systems (ECIS) 24, 2016
Do you comply with AI? - Personalized explanations of learning algorithms and their impact on employees' compliance behavior
N Kühl, J Lobana, C Meske
40th International Conference on Information Systems (ICIS), 2019
How to cope with change?-preserving validity of predictive services over time
L Baier, N Kühl, G Satzger
Hawaii International Conference on System Sciences, 2019
Designing transparency for effective human-AI collaboration
M Vössing, N Kühl, M Lind, G Satzger
Information Systems Frontiers 24 (3), 877-895, 2022
Cognitive computing for customer profiling: meta classification for gender prediction
R Hirt, N Kühl, G Satzger
Electronic Markets 29 (1), 93-106, 2019
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