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 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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Is VQA quicker than classical machine learning?

Variational Quantum Algorithm (VQA) is a kind of quantum algorithm corresponding to classical machine learning. Unlike the square speed up of Grover's algorithm, the circuit in VQA does not seem to ...
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129 views

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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49 views

Does anyone know how to use TF Quantum with real hardware data?

I'm currently trying to embed a tensorflow model for denoising measurements as a tensorflow quantum model, and at some point I'd like for this to be able to run on hardware. After reading through all ...
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57 views

Reconstructing classical data from quantum feature maps

In the paper [Supervised learning with quantum enhanced feature spaces (Nature, arxiv) by Havlicek et al., a feature map is defined by $$| \Phi(\bar{x})\rangle=U_{\Phi(\bar x)}H^{\otimes n} U_{\Phi(\...
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240 views

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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10 views

Implementation of Quantum PAC learning classifier

I am working on a project related to Boosting of Quantum Classifiers of PAC format. And I am a little confused about how do we go about implementing a PAC classifier. The basic idea is that we have to ...
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53 views

Qiskit's classifier is not optimising the weights

I am using qiskit's VQC to build a classifier. Dimensionality of the data is 2 and number of classes are 4. The feature map I used is ZZFeatureMap and ansatz is the RealAplitudes. Then entanglement ...
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39 views

Quantum Machine Learning: how to get effective time of training/scoring

I am trying to examine the potential of Quantum Machine learning in terms of performance and time compared to classical algorithms. I am using both Qiskit's QSVM and scikit's SVM with Qiskit Quantum ...
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44 views

What is the kernel used in the IBM Qiskit's source code?

I want to redefine the QSVM code for a different kernel. But what is the kernel actually used in the IBM Qiskit's source code? And where is it defined, exactly. QSVM on Qiskit.
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31 views

Methods for encoding non-linear probabilities as data

I am working on translating a computing method I developed to model complex non-linear systems with classical computational methods into a form that is natural to quantum computing. The technique ...
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27 views

Parameterized swap test and perfect swap test

Suppose one has parameterized a swap test by using an ansatz $U(\theta) = \exp(-i\theta \text{ CSWAP})$, and one tries to find an angle $\theta$ such that one can distinguish given two quantum states ...
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Quantum GAN implementation

Can anyone provide a good link to understand how to implement qgan using pytorch in qiskit. Trying to understand this ( https://qiskit.org/documentation/machine-learning/tutorials/...
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33 views

How to perform multi-class classification with qiskit's VQC?

I am following the tutorial given in qiskit's website Neural Network Classifier and Regressor. In the first part, classification, the third section refers to qiskit's VQC library. Everything works ...
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28 views

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 ...
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39 views

Quantum Boltzmann Machine and Gibbs state

I was looking into Quantum Boltzmann Machine and ran into Gibbs State as a part of training. Since new to this field, it would be good to have good intuitions why Gibbs state is related. Is Gibbs ...
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66 views

How do we implement QKNN algorithm on our dataset

What could be the steps to implement a distance based classifier (eg Qknn) on our dataset using quantum computing? I read a paper on "Distance based classifier using Iris dataset". I wanted ...