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# Abstract
In recent years, the application of machine learning and deep learning to classical cryptanalysis is an active research field.
In this project, we perform quantum cryptanalysis that combi…
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I created a quantum neural network using tensorflow quantum,It's input is a tensor converted by circuit.About this input circuit,I found that if the parameters of the circuit are also specified by te…
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# Description
Write the Quantum Neural Network section for the Qiskit Textbook Quantum Machine Learning chapter. This will comprise of 2-3 pages, introducing quantum neural networks, building one fro…
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Please add explicit support for graph-structured data including
- quantum graph kernels
- quantum graph neural networks, particularly quantum graph convolutional networks
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### Team Name:
*Qming*
### Project Description:
The goal of this project is to explore and demonstrate the advantage of hybrid quantum-classical neural network (QCNN) over classical models …
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I have taken a closer look at your quantum neural network architecture, which is of great help to my research, do you have a paper on this architecture, I would like to see a specific paper.
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### Expected behavior
It is expected that no gates will be added by calling qml.pauli.string_to_pauli_word() in a circuit.
```
import pennylane as qml
dev = qml.device("default.qubit", wires=3…
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**Title` of the quantum algorithm**
Demonstration for Quantum Convolutional Neural Network with Chest X-ray Pneumonia Dataset
**Description of the quantum algorithm**
Quantum Convolutional Neur…
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# Abstract
Let's try and explore Hybrid quantum-classical Neural Networks with PyTorch and Qiskit:
https://qiskit.org/textbook/ch-machine-learning/machine-learning-qiskit-pytorch.html
Examples:
…
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#### Issue description
when i use the lightning.qubit device i got the error below i already install `pennylane-lightning` latest version.
#### Source code and tracebacks
```python
import penny…