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sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering]
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DOI：10.1109/MS.2025.3527736.png)
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Abstract
En 中文
sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine learning tools like scikit-learn. The library’s dual-layer architecture serves both QML researchers and practitioners, enabling efficient prototyping, experimentation, and pipelining.
Keywords:
Encoding
Quantum computing
Engines
Computational modeling
Hardware
Libraries
Mathematical models
Training
Qubit
Python
Machine learning
Journal
IF:
3
Papers:
3.2K
Citations:
3.6K