Questions tagged [quantum-enhanced-machine-learning]

For questions about quantum algorithms tackling machine learning tasks (e.g. the HHL algorithm or questions about quantum neural networks). For questions about applying classical machine learning to quantum-information-related problems, use machine-learning instead.

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What is a “repeat until success quantum circuit” in quantum neural networks?

I am working now on a quantum neural network project and want a deep explanation on the Repeat Until Success circuit. What I know about this circuit is that it allows a nonlinear activation function ...
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Usage of Tensorflow/Keras to train Qiskit circuits

In order to explore whether it is possible to train a Qiskit Quantum circuit with tensorflow I built a small toy model. The purpose of this toy model is to find via tensorflow the correct angle to get ...
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Comparing QSVM & Classic SVM on BigData. Quantum Supremacy

I work on comparing QSVM and Classic SVM (SKlearnSVM) with using Qiskit. I have to show quantum supremacy at 400000-500000 samples but I don't get good results. I have problem with long time training ...
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What is the advantage of QSVM over the classical SVM?

I am mainly talking about QSVM from Qiskit (https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.QSVM.html#qiskit.aqua.algorithms.QSVM) versus a classical SVM. Is it just a time complexity ...
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What is the advantage of quantum machine learning over traditional machine learning?

Why exactly is machine learning on quantum computers different than classical machine learning? Is there a specific difference that allows quantum machine learning to outperform classical machine ...
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What are the benefits of using quantum machine learning?

I have been investigating uses for quantum machine learning, and have made a few working examples (variations of variational quantum classifiers using PennyLane). However, my issue now is its ...
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Qiskit QSVM - Alphas and Support Vectors [closed]

I just started using Qiskit and I have implemented the QSVM example. However, I having trouble with the return. The qsvm.predict() results are reasonable but when ...
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Calculating gradient of a gate using Parameter shift rule

I've been following this website to check out how parameter-shift works for calculation of gradients for backpropagation in Variational Quantum Machine Learning Circuits Most of it made makes sense ...
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Comparison of matrix inversion algorithms

Since 2009, many matrix inversion algorithms have appeared. Is there somewhere a table, or recently released overview, comparing the speed of matrix inversion algorithms, like done in this table taken ...
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Why is Farhi and Neven's architecture described in “Classification with Quantum Neural Network on near term processors” called a Neural Network?

In regards to "Classification with Quantum Neural Networks on near term processors" (which you can find here) , there are still a few things that do not make entirely sense to me. First of all, why ...
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How is data encoded in a quantum neural network?

I am a newbie to quantum machine learning. I am trying to build a quantum neural network (QNN). What I studied so far about QNN is that input would be qubits and hidden layer parameter can be set ...
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Regarding quantum support vector machine using qiskit [duplicate]

I would like to ask, how can I add my own .csv data file to run a quantum support vector machine using qiskit ? I don't want to use already existing datasets in sklearn, scikit-learn library.
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Quantum PCA State Preparation

In Quantum Algorithm Implementations for Beginners is an example of the Quantum PCA with an given 2 x 2 covariance matrix $\sum$. The steps for state preparation are given in the paper. The steps are: ...
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Quantum machine learning after Ewin Tang

Recently, a series of research papers have been released (this, this and this, also this) that provide classical algorithms with the same runtime as quantum machine learning algorithms for the same ...
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Are there any examples of anyone applying quantum algorithms to problems in computational biology?

As the title suggests, I'm searching for published examples of quantum algorithms being applied to problems in computational biology. Clearly the odds are high that practical examples don't exist (yet)...
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HHL algorithm — controlled-by-eigenvalues rotations

All the references in this question refer to Quantum algorithm for solving linear systems of equations (Harrow, Hassidim & Lloyd, 2009). The question I have is about the step where they apply ...
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Barren plateaus in quantum neural network training landscapes

Here the authors argue that the efforts of creating a scalable quantum neural network using a set of parameterized gates are deemed to fail for a large number of qubits. This is due to the fact that, ...
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Introductory material for quantum machine learning

In the past few days, I have been trying to collect material (mostly research papers) related to Quantum machine learning and its applications, for a summer project. Here are a few which I found ...
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Will deep learning neural networks run on quantum computers?

Deep Learning (multiple layers of artificial neural networks used in supervised and unsupervised machine learning tasks) is an incredibly powerful tool for many of the most difficult machine learning ...
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Is there any potential application of quantum computers in machine learning or AI?

A lot of people believe that quantum computers can prove to be a pivotal step in creating new machine learning and AI algorithms that can give a huge boost to the field. There have even been studies ...