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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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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 ...
Sanchayan Dutta's user avatar
29 votes
3 answers
2k views

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 ...
Piyush Kathuria's user avatar
43 votes
1 answer
2k views

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 ...
Alex's user avatar
  • 543
15 votes
5 answers
4k views

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 ...
Bob Swain's user avatar
  • 253
10 votes
2 answers
1k views

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 ...
Rob James's user avatar
  • 355
15 votes
4 answers
2k views

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)...
Greenstick's user avatar
  • 1,086
10 votes
2 answers
507 views

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 ...
Andrew's user avatar
  • 333
5 votes
1 answer
388 views

Applications of Quantum Principal Component Analysis

I have been reading Seth Lloyd's paper on Quantum Principal Component Analysis and while there is a short discussion that points to possible applications, I am having a hard time seeing the advantage ...
Song of Physics's user avatar
4 votes
1 answer
899 views

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 ...
Adrien Suau's user avatar
  • 4,987
1 vote
2 answers
551 views

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/...
user14924's user avatar
  • 317
13 votes
1 answer
1k views

Comparing method of differentiation in variational quantum circuit

Training of variational circuits needs to calculate the derivative to be optimized. Several methods were proposed (1), the most famous ones being the finite difference and the parameter shift rule. ...
incud's user avatar
  • 741
10 votes
1 answer
672 views

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, ...
asdf's user avatar
  • 503
6 votes
0 answers
234 views

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 ...
narip's user avatar
  • 2,999
5 votes
1 answer
251 views

Are there quantum algorithms demonstrating speedup computing classical neural networks (in 2021)?

It seems like there are a number of different speed-ups for different machine learning algorithms: But has anyone created an algorithm showing speed-up for neural networks? A similar question was ...
Steven Sagona's user avatar
4 votes
1 answer
3k views

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 ...
Muhammad Kashif's user avatar
3 votes
1 answer
143 views

Advantage of density matrix over vector to form quantum kernel

In Maria Schuld, Supervised quantum machine learning models are kernel methods, Section III.A, on page 6, the third paragraph from the bottom states While from a quantum physics perspective it seems ...
Hans's user avatar
  • 217
2 votes
1 answer
2k views

Quantum circuit for the ZZ feature map

Havlicek et al. propose a feature map for embedding $n$-dimensional classical data on $n$ qubits: $U_{\phi(x)}H^{\otimes n}$, where $$ U_{\phi(x)} = \exp (i \sum_{S \subseteq [n]} \phi_S(x) \prod_{i \...
lazybvr's user avatar
  • 23
2 votes
1 answer
168 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 ...
Harsha Pamidipalli's user avatar
1 vote
0 answers
56 views

The possibility of an image classifier using quantum computer architecture?

Consider an exhaustive database of all contour images that can ever be created on a 16x16 grid. Out of the $2^{256}$ unique possibilities, could a quantum computer classify all the resulting images ...
LithiumPoisoning's user avatar
1 vote
1 answer
136 views

Error loading saved hybrid quantum (pennylane + tensorflow keras) model: Unknown layer: 'KerasLayer'

I'm creating a hybrid model consisting of classical convolutional layers and a quantum output using Tensorflow. I can save the model in either .h5 or .keras format, but when I load them with the code <...
Ryan Wang's user avatar
  • 247
1 vote
1 answer
141 views

How to save a hybrid Tensorflow and Pennylane model?

I implemented a hybrid model with Keras and Pennylane that looks like this: The quantum layer is basically a quantum circuit converted to a keras layer with the ...
Ryan Wang's user avatar
  • 247
1 vote
1 answer
609 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 ...
Harsha Pamidipalli's user avatar
1 vote
0 answers
98 views

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.
vis555's user avatar
  • 53