mlsanityData to 14 Oct 2026

Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators

arXiv 2505.17756 ↗First posted 23 May 2025quant-ph cs.ET cs.LGcited by 7

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Abstract (arXiv)

We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primitives to facilitate interactions with classical simulators and quantum hardware. Qiskit ML started as a proof-of-concept code in 2019 and has since been developed to be a modular, intuitive tool for non-specialist users while allowing extensibility and fine-tuning controls for quantum computational scientists and developers. The library is available as a public, open-source tool and is distributed under the Apache version 2.0 license.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 13 of its 37 references that are in the map. First posted on arXiv 23 May 2025.

Builds on

13 of 37 references.

References · 13

  1. 2018Supervised learning with quantum enhanced feature spacescited by 665
  2. 2020The power of quantum neural networkscited by 379
  3. 2020A rigorous and robust quantum speed-up in supervised machine learningcited by 271
  4. 2014Quantum Inference on Bayesian Networkscited by 19
  5. 2022Quantum Machine Learning Framework for Virtual Screening in Drug Discovery: a Prospective Quantum Advantagecited by 18
  6. 2023Quantum Kernel Alignment with Stochastic Gradient Descentcited by 14
  7. 2020When Machine Learning Meets Quantum Computers: A Case Studycited by 9
  8. 2020Quantum circuit representation of Bayesian networkscited by 7
  9. 2024Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Trainingcited by 6
  10. 2024Symmetry breaking in geometric quantum machine learning in the presence of noisecited by 5
  11. 2024Quantum Convolutional Neural Networks for the detection of Gamma-Ray Bursts in the AGILE space mission datacited by 2
  12. 2023Quantum Text Classifier -- A Synchronistic Approach Towards Classical and Quantum Machine Learningcited by 1
1 more
  1. 2025Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detectioncited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2025Comparative Analysis of QNN Architectures for Wind Power Prediction: Feature Maps and Ansatz Configurationscited by 2
  2. 2025From Classical to Hybrid: A Practical Framework for Quantum-Enhanced Learningcited by 1
  3. 2025Modeling Quantum Autoencoder Trainable Kernel for IoT Anomaly Detectioncited by 0
  4. 2026Efficient Mutation Testing of Quantum Machine Learning Modelscited by 0
  5. 2026Quantum-classical hybrid models based on error correction for time series forecastingcited by 0
  6. 2026Towards quantum machine learning for assessing the resilience of post-quantum cryptographycited by 0
  7. 2026Impact of Data Loss in Postprocessing on Training and Inference of Quantum Neural Networkscited by 0