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2020 – today
- 2023
[c10]Lucas Baier, Tim Schlör, Jakob Schoeffer, Niklas Kühl:
Detecting Concept Drift with Neural Network Model Uncertainty. HICSS 2023: 835-844- 2022
- [j2]Niklas Kühl
, Marc Goutier, Lucas Baier, Clemens Wolff, Dominik Martin:
Human vs. supervised machine learning: Who learns patterns faster? Cogn. Syst. Res. 76: 78-92 (2022) - 2021
- [b1]Lucas Baier:
Concept Drift Handling in Information Systems: Preserving the Validity of Deployed Machine Learning Models. Karlsruhe Institute of Technology, Germany, 2021 - [j1]Niklas Kühl, Robin Hirt, Lucas Baier, Björn Schmitz, Gerhard Satzger:
How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Report Card. Commun. Assoc. Inf. Syst. 48: 46 (2021) - [c9]Max Schemmer, Daniel Heinz, Lucas Baier, Michael Vössing, Niklas Kühl:
Conceptualizing Digital Resilience for AI-based Information Systems. ECIS 2021 - [c8]Lucas Baier, Vincent Kellner, Niklas Kühl, Gerhard Satzger:
Switching Scheme: A Novel Approach for Handling Incremental Concept Drift in Real-World Data Sets. HICSS 2021: 1-10 - [c7]Lucas Baier, Niklas Kühl, Jörg Schmitt:
Increasing Robustness for Machine Learning Services in Challenging Environments: Limited Resources and No Label Feedback. IntelliSys (1) 2021: 837-856 - [i6]Lucas Baier, Tim Schlör, Jakob Schöffer, Niklas Kühl:
Detecting Concept Drift With Neural Network Model Uncertainty. CoRR abs/2107.01873 (2021) - 2020
- [c6]Lucas Baier, Jakob Schöffer, Niklas Kühl:
Utilizing Adaptive AI-based Information Systems to Analyze the Effectiveness of Policy Measures in the Fight of COVID-19. ICIS 2020 - [c5]Lucas Baier, Josua Reimold, Niklas Kühl:
Handling Concept Drift for Predictions in Business Process Mining. CBI (1) 2020: 76-83 - [c4]Lucas Baier, Niklas Kühl, Gerhard Satzger, Marcel Hofmann, Marisa Mohr:
Handling Concept Drifts in Regression Problems - the Error Intersection Approach. Wirtschaftsinformatik (Zentrale Tracks) 2020: 210-224 - [i5]Lucas Baier, Marcel Hofmann, Niklas Kühl, Marisa Mohr, Gerhard Satzger:
Handling Concept Drifts in Regression Problems - the Error Intersection Approach. CoRR abs/2004.00438 (2020) - [i4]Lucas Baier, Josua Reimold, Niklas Kühl:
Handling Concept Drift for Predictions in Business Process Mining. CoRR abs/2005.05810 (2020) - [i3]Lucas Baier, Vincent Kellner, Niklas Kühl, Gerhard Satzger:
Switching Scheme: A Novel Approach for Handling Incremental Concept Drift in Real-World Data Sets. CoRR abs/2011.02738 (2020) - [i2]Niklas Kühl, Marc Goutier, Lucas Baier, Clemens Wolff, Dominik Martin:
Human vs. supervised machine learning: Who learns patterns faster? CoRR abs/2012.03661 (2020) - [i1]Lucas Baier, Niklas Kühl, Jakob Schöffer, Gerhard Satzger:
Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic. CoRR abs/2012.03728 (2020)
2010 – 2019
- 2019
- [c3]Lucas Baier, Fabian Jöhren, Stefan Seebacher:
Challenges in the Deployment and Operation of Machine Learning in Practice. ECIS 2019 - [c2]Lucas Baier, Niklas Kühl, Gerhard Satzger:
How to Cope with Change? - Preserving Validity of Predictive Services over Time. HICSS 2019: 1-10 - 2017
- [c1]Phani Kishore Gadepalli, Robert Gifford, Lucas Baier, Michael Kelly, Gabriel Parmer:
Temporal Capabilities: Access Control for Time. RTSS 2017: 56-67
Coauthor Index
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