This repository containes examples for quantum computing applications in machine learning.
Currently contains:
- Heirarchical Quantum Classifiers by Grant et al.: MERA and TTN inspired PQC for binary classification on IRIS and MNIST datasets.
- Quantum Kitchen Sinks by Wilson et al.: Contains a quantum kitchen sinks example for binary classification on MNIST.
- A parameterised quantum circuit for learning an arbitrary unknown state. Trained using gradient descent with the parameter shift method to find the parameters for the PQC.
tensorflow-quantum, scipy, sklearn, keras, cirq, qiskit
- Add noise models for simulations.
- QEC with Quantum Convolutional Neural networks from Cong et al.
- Universal discriminative quantum neural networks by Chen et al.
- Circuit-centric quantum classifiers by Schuld et al.
- Quantum Boltzmann machines
- Quantum Circuit Born machine
- Quantum Neural Networks to simulate many-body physics by Gardas et al.
- Generative models from Bendetti's PhD Thesis