David Kreplin

According to our database, David Kreplin authored at least 8 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Quantum Deep Learning: A Comprehensive Review.

Yanjun Ji, Zhao-Yun Chen, Marco Roth, David A. Kreplin, Christian Schiffer, Martin King, Oliver Anton, M. Sahnawaz Alam, Markus Krutzik, Dennis Willsch, Ludwig Mathey, Frank K. Wilhelm, Guo-Ping Guo

CoRR, March, 2026

An Introduction to Quantum Computing.

David A. Kreplin

Proceedings of the What if... How could quantum computing change computer science?, 2026

2025

AutoQML: A Framework for Automated Quantum Machine Learning.

Marco Roth, David A. Kreplin, Daniel Basilewitsch, João F. Bravo, Dennis Klau, Milan Marinov, Daniel Pranjic, Horst Stühler, Moritz Willmann, Marc-André Zöller

CoRR, February, 2025

sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering].

David A. Kreplin, Moritz Willmann, Jan Schnabel, Frederic Rapp, Manuel Hagelüken, Marco Roth

IEEE Softw., 2025

Reinforcement learning-based architecture search for quantum machine learning.

Frederic Rapp, David A. Kreplin, Marco F. Huber, Marco Roth

Mach. Learn. Sci. Technol., 2025

AutoQML: A Framework for Automated Quantum Machine Learning.

Marco Roth, David A. Kreplin, Daniel Basilewitsch, João F. Bravo, Dennis Klau, Milan Marinov, Daniel Pranjic, Peter Schichtel, Horst Stühler, Moritz Willmann, Marc-André Zöller

Proceedings of the IEEE International Conference on Quantum Software, 2025

2024

Reduction of finite sampling noise in quantum neural networks.

David A. Kreplin, Marco Roth

Quantum, 2024

2023

sQUlearn - A Python Library for Quantum Machine Learning.

David A. Kreplin, Moritz Willmann, Jan Schnabel, Frederic Rapp, Marco Roth

CoRR, 2023