Transfer learning in hybrid classical-quantum neural networks
Open accessAbstract
We extend the concept of transfer learning, widely applied in modern machine learning algorithms, to the emerging context of hybrid neural networks composed of classical and quantum elements. We propose different implementations of hybrid transfer learning, but we focus mainly on the paradigm in which a pre-trained classical network is modified and augmented by a final variational quantum circuit. This approach is particularly attractive in the current era of intermediate-scale quantum technology since it allows to optimally pre-process high dimensional data (e.g., images) with any state-of-the-art classical network and to embed a select set of highly informative features into a quantum processor. We present several proof-of-concept examples of the convenient application of quantum transfer learning for image recognition and quantum state classification. We use the cross-platform software library PennyLane to experimentally test a high-resolution image classifier with two different quantum computers, respectively provided by IBM and Rigetti.
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The hybrid transfer learning strategy was demonstrated on Rigetti and IBM machines with success.
“Even though this reasonable hybrid strategy was demonstrated on Rigetti and IBM machines with success [64]”
From Quantum computing algorithms: getting closer to critical problems in computational biology (2022) · cites this paper as [64]
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Mitigating barren plateaus with transfer-learning-inspired parameter initializations
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Bayesian Quantum Neural Networks
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Bibliometric Survey of Quantum Machine Learning
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Hybrid Quantum-Classical Neural Network for Cloud-Supported In-Vehicle Cyberattack Detection
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Quantum Transfer Learning for Real-World, Small, and High-Dimensional Remotely Sensed Datasets
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Quantum-enhanced deep neural network architecture for image scene classification
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Hybrid Quantum-Classical Neural Networks for Downlink Beamforming Optimization
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Completely quantum neural networks
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Quantum Graph Neural Network Models for Materials Search
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Hybrid quantum neural network structures for image multi-classification
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Hybrid Classical–Quantum Transfer Learning for Cardiomegaly Detection in Chest X-rays
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A Characterization of Quantum Generative Models
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Classical–Quantum Transfer Learning for Image Classification
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Quantum architecture search via truly proximal policy optimization
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A Quantum-Classical Hybrid Solution for Deep Anomaly Detection
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Architectural Vision for Quantum Computing in the Edge-Cloud Continuum
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QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train
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A classical–quantum convolutional neural network for detecting pneumonia from chest radiographs
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Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware with GPU Acceleration
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Exploiting the Quantum Advantage for Satellite Image Processing: Review and Assessment
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Hybrid quantum-classical classifier based on tensor network and variational quantum circuitPreprint
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EEG-based motor imagery classification with quantum algorithms
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Hybrid Quantum Network for classification of finance and MNIST data
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A Quantum-Classical Hybrid Method for Image Classification and Segmentation
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Warm-Starting and Quantum Computing: A Systematic Mapping Study
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Time Series Forecasting with Quantum Machine Learning Architectures
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On Depth, Robustness and Performance Using the Data Re-Uploading Single-Qubit Classifier
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The impact of cost function globality and locality in hybrid quantum neural networks on NISQ devices
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Toward Quantum-Native Communication Systems: State-of-the-Art, Trends, and Challenges
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Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction
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Scalable parameterized quantum circuits classifier
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Quantum Transfer Learning for Wi-Fi Sensing
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Quantum–Classical Image Processing for Scene Classification
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- Authors
- Mari, A., Bromley, T. R., Izaac, J., Schuld, M., & Killoran, N.
- Affiliations
- Xanadu Quantum Technologies (Canada) (CA)
- Venue
- Quantum
- Published
- 2020-10-09
- Volume
- 4
- Pages
- 340
- ISSN
- 2521-327X (ISSN-L)
- OpenAlex
- W2995742898
- Cited by
- 435
- References
- 52
- Citations by year
- 2026: 95 · 2025: 104 · 2024: 69 · 2023: 69 · 2022: 49 · 2021: 35 · 2020: 13 · 2019: 1
- FWCI
- 16.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Quantum (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Unicam Scientific Publications (University of Camerino) (submittedVersion, other-oa)
- arXiv (Cornell University) (cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- transfer learning, hybrid quantum-classical neural networks, variational quantum circuits, image classification, quantum state classification, PennyLane
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