Folgen
Kai Heinrich
Titel
Zitiert von
Zitiert von
Jahr
Machine learning and deep learning
C Janiesch, P Zschech, K Heinrich
Electronic Markets 31 (3), 685-695, 2021
14662021
Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability
LV Herm, K Heinrich, J Wanner, C Janiesch
International Journal of Information Management 69, 102538, 2023
552023
Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning
K Heinrich, P Zschech, C Janiesch, M Bonin
Decision Support Systems 143, 113494, 2021
422021
How Much AI Do You Require? Decision Factors for Adopting AI Technology.
J Wanner, K Heinrich, C Janiesch, P Zschech
ICIS, 2020
352020
White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems.
J Wanner, LV Herm, K Heinrich, C Janiesch, P Zschech
ICIS, 2020
352020
Intelligent user assistance for automated data mining method selection
P Zschech, R Horn, D Höschele, C Janiesch, K Heinrich
Business & Information Systems Engineering 62, 227-247, 2020
282020
Prognostic model development with missing labels: a condition-based maintenance approach using machine learning
P Zschech, K Heinrich, R Bink, JS Neufeld
Business & Information Systems Engineering 61, 327-343, 2019
242019
Analyzing customer sentiments in microblogs–A topic-model-based approach for Twitter datasets
S Sommer, A Schieber, A Hilbert, K Heinrich
242011
The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study
J Wanner, LV Herm, K Heinrich, C Janiesch
Electronic Markets 32 (4), 2079-2102, 2022
232022
Everything counts: a Taxonomy of Deep Learning Approaches for Object Counting.
K Heinrich, A Roth, P Zschech
ECIS, 2019
192019
Demystifying the black box: A classification scheme for interpretation and visualization of deep intelligent systems
K Heinrich, P Zschech, T Skouti, J Griebenow, S Riechert
182019
A picture is worth a collaboration: Accumulating design knowledge for computer-vision-based hybrid intelligence systems
P Zschech, J Walk, K Heinrich, M Vössing, N Kühl
arXiv preprint arXiv:2104.11600, 2021
172021
What is the conversation about?: A topic-model-based approach for analyzing customer sentiments in twitter
S Sommer, A Schieber, K Heinrich, A Hilbert
International Journal of Intelligent Information Technologies (IJIIT) 8 (1 …, 2012
172012
Stop ordering machine learning algorithms by their explainability! An empirical investigation of the tradeoff between performance and explainability
J Wanner, LV Herm, K Heinrich, C Janiesch
Conference on e-Business, e-Services and e-Society, 245-258, 2021
152021
Towards a Taxonomic Benchmarking Framework for Predictive Maintenance: The Case of NASA's Turbofan Degradation.
P Zschech, J Bernien, K Heinrich
ICIS, 2019
142019
Are you up for the challenge? Towards the development of a big data capability assessment model
P Zschech, K Heinrich, M Pfitzner, A Hilbert
142017
Fool me Once, shame on You, Fool me Twice, shame on me: a Taxonomy of Attack and de-Fense Patterns for AI Security.
K Heinrich, J Graf, J Chen, J Laurisch, P Zschech
ECIS, 2020
122020
Yield prognosis for the agrarian management of vineyards using deep learning for object counting
K Heinrich, A Roth, L Breithaupt, B Möller, J Maresch
122019
A social evaluation of the perceived goodness of explainability in machine learning
J Wanner, LV Herm, K Heinrich, C Janiesch
Journal of Business Analytics 5 (1), 29-50, 2022
112022
Is bigger always better? Lessons learnt from the evolution of deep learning architectures for image classification
K Heinrich, B Möller, C Janiesch, P Zschech
102019
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20