4 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Quantum Neural Networks in Practice: A Comparative Study with Classical Models from Standard Data Sets to Industrial Images
Daniel Basilewitsch, João F. Bravo, Christian Tutschku +1
We compare the performance of randomized classical and quantum neural networks (NNs) as well as classical and quantum-classical hybrid convolutional neural networks (CNNs) for the…
Ion-Based Quantum Computing Hardware: Performance and End-User Perspective
Thomas Strohm, Karen Wintersperger, Florian Dommert +6
This is the second paper in a series of papers providing an overview of different quantum computing hardware platforms from an industrial end-user perspective. It follows our first…
Comparing planar quantum computing platforms at the quantum speed limit
Daniel Basilewitsch, Clemens Dlaska, Wolfgang Lechner
An important aspect that strongly impacts the experimental feasibility of quantum circuits is the ratio of gate times and typical error time scales. Algorithms with circuit depths…