https://github.com/boltzmannentropy/qugel
This work presents Qugel , a QML platform which utilizes shallow quantum neural network (QNN) image encoders composed of parametrized quantum circuits (PQCs) for solving Kaggle categorial image classification challenges.
https://github.com/boltzmannentropy/qugel
ai convolutional-neural-networks deep-learning entanglement kaggle kaggle-competition pennylane python pytorch qml quantum quantum-autoencoer quantum-computing quantum-machine-learning quanvolutional quanvolutional-neural-networks superposition
Last synced: 6 months ago
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This work presents Qugel , a QML platform which utilizes shallow quantum neural network (QNN) image encoders composed of parametrized quantum circuits (PQCs) for solving Kaggle categorial image classification challenges.
- Host: GitHub
- URL: https://github.com/boltzmannentropy/qugel
- Owner: BoltzmannEntropy
- License: other
- Created: 2023-06-11T05:02:35.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2023-06-18T18:15:05.000Z (over 2 years ago)
- Last Synced: 2023-06-18T23:04:10.971Z (over 2 years ago)
- Topics: ai, convolutional-neural-networks, deep-learning, entanglement, kaggle, kaggle-competition, pennylane, python, pytorch, qml, quantum, quantum-autoencoer, quantum-computing, quantum-machine-learning, quanvolutional, quanvolutional-neural-networks, superposition
- Language: Jupyter Notebook
- Homepage:
- Size: 14.8 MB
- Stars: 9
- Watchers: 3
- Forks: 3
- Open Issues: 0