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Questions tagged [quantum-neural-network]

A machine learning model or algorithm that combines concepts from quantum computing and artificial neural networks encompassing a variety of ideas, ranging from quantum computers emulating the exact computations of neural nets, to general trainable quantum circuits that bear only little resemblence with the multi-layer perceptron structure.

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Equivalencies between neural networks and quantum neural networks

TL;DR - Quantum neural networks use a few qubits, gates and simple quantum circuits. Regular neural networks use real numbers (composed of many bits), nonlinear functions on real numbers and very ...
sheesymcdeezy's user avatar
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Is entanglement trainable?

There exists a famous result from Google that the gradients of the parameters of quantum neural networks (QNN) vanish exponentially with the number of qubits in the quantum circuit. Their result ...
jsbaker's user avatar
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Quantum Convolutional Neural Network not producing gradients

I am trying to bulid a quantum convolutional neural network for image classification with Pennylane and Keras but the model isn't training and I keep getting the warning: WARNING:tensorflow:Gradients ...
Umm's user avatar
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How to take gradient of the `tfq.layers.State` output?

I am using the following code for building a quantum circuit as a custom tf.keras.layers.Layer: ...
Shuhul Handoo's user avatar
2 votes
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How can we compute the gradient in a Quantum RNN?

I was looking into implementing a quantum recurrent neural network (QRNN) for a project, but I have some doubts about the computation of the gradient. There are a few papers that have implemented a ...
Alex Li's user avatar
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Adding trainable weights to feature inputs for a CircuitQNN?

Currently I'm trying to get together a QNN that can be trained to classify the normalized (-1, 1) IRIS Dataset on all 3 classes. For this I am using Qiskit's ...
Ricardo's user avatar
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What is the input for the interpret of Quantum Variational Regressors?

I'm trying to implement my first variational regressor using qiskit. I would like to understand how the interpret of a CircuitQNN works. I need to define an interpret that works on the amplitudes of a ...
Roberto Schiattarella's user avatar
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Implementation of identity block initialisation strategy for mitigating barren plateaus

I have been trying to implement this paper on identity block initialisation strategy for barren plateau mitigation but I don't really understand how one would apply it to a parameterised circuit with ...
Moto's user avatar
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Adding an Extra Qubit into a Quantum Circuit

I am a beginner in quantum computing and am learning about parameterised quantum circuits (in the context of quantum neural networks). What effect does adding an extra qubit into a quantum circuit ...
Rij's user avatar
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Effect of error correction gates in QCNN

In Iris Cong et. al. (2019) they propose a Quantum Convolutional Neural Network that utilizes mid-circuit measurements to control an error-correcting ansatz $V_j$. This is the equivalent of a pooling ...
Federico Tiblias's user avatar
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Measuring a single-qubit PauliZ using Qiskit's EstimatorQNN

I am currently working with the EstimatorQNN from Qiskit to construct a Quantum Neural Network using a custom Parametrized Quantum Circuit. But I want to change the ...
yeray142's user avatar
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Where is the input data X in the CV-QNN as presented in Pennylane?

I am referring to the tutorial of CV-QNN in Pennylane(Strawberry Fields). Each layer of CV-QNN can perform the operation below. Unlike other quantum neural network tutorials, where the input X and y ...
user48217's user avatar
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Quantum Generative Adversarial Network does not converge

I have built a quantum generative adversarial network model, in which the generator and the discriminator, both are quantum based model. The parametrized quantum circuit/ansatz of these two models are ...
Shuhul Handoo's user avatar
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How to train a Quantum Neural network for regression model in supervised learning

We want to train a parameterised circuit(which is our neural network - from this paper. Now our final circuit looks a little like Let's say there are n training cases. So I have n |gt> vectors ...
Parmeet Singh EP 066's user avatar
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Quantum data as input for Quantum Neural Net

I'm new to quantum machine learning, and I wanted to know how quantum data is processed in a quantum neural net. For example, if I am training a QNN to classify entangled circuits from non-entangled ...
beginnerCoder7's user avatar
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tensorflow, tensorflow-quantum, tensorflow-federated latest version compatibility?

I have been working with on some research on tensorflow, tensorflow-quantum and tensorflow-federated and the problem with that is I just can't install those three at my google colab and I tried ...
Rayhan's user avatar
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