4 citations · 8 across the 4 of their papers we have counts for
4 papers
AutoQML: A Framework for Automated Quantum Machine Learning
Marco Roth, David A. Kreplin, Daniel Basilewitsch +7
Automated Machine Learning (AutoML) has significantly advanced the efficiency of ML-focused software development by automating hyperparameter optimization and pipeline construction…
Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors
Daniel Pranjić, Florian Knäble, Philipp Kunst +6
Whether in fundamental physics, cybersecurity or finance, the detection of anomalies with machine learning techniques is a highly relevant and active field of research, as it poten…
Bringing Quantum Algorithms to Automated Machine Learning: A Systematic Review of AutoML Frameworks Regarding Extensibility for QML Algorithms
Dennis Klau, Marc Zöller, Christian Tutschku
This work describes the selection approach and analysis of existing AutoML frameworks regarding their capability of a) incorporating Quantum Machine Learning (QML) algorithms into…
Benchmarking Automated Machine Learning Methods for Price Forecasting Applications
Horst Stühler, Marc-André Zöller, Dennis Klau +2
Price forecasting for used construction equipment is a challenging task due to spatial and temporal price fluctuations. It is thus of high interest to automate the forecasting proc…