Questions tagged [neural-network]

Use this tag for questions about possible applications of quantum computing in improving neural network models and/or quantum neural networks. Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems "learn" (i.e. progressively improve performance on) tasks by considering examples, generally without task-specific programming (Wikipedia).

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3
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0answers
33 views

How to derive a circuit from given equations?

I was reading a paper on Quantum Neural Networks where the authors discussed a new back propagation algorithm. They shared a schematic of the circuit. However, I am unable to understand how the ...
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How to encode MNIST data set on a quantum circuit to study supervised learning with QNN?

I am trying to implement arXiv:1802.06002†. I do not understand how to take the data set from MNIST and apply it to a quantum circuit. [†]: Classification with Quantum Neural Networks on Near Term ...
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Can quantum annealing be used for training convolutional neural networks?

Simulated annealing is applied for deep learning using convolutional neural networks. Likewise, can quantum annealing be used? These two papers: Simulated Annealing Algorithm for Deep Learning (...
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299 views

Quantum algorithm for linear systems of equations (HHL09): Step 1 - Number of qubits needed

This is a continuation of Quantum algorithm for linear systems of equations (HHL09): Step 1 - Confusion regarding the usage of phase estimation algorithm Questions (contd.): Part 2: I'm not exactly ...
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1answer
530 views

Is it possible to speed up the generation of the weighting matrix using a quantum algorithm?

In this[1] paper, on page 2, they mention that they are generating the weighting matrix as follows: $$W = \frac{1}{Md}[\sum_{m=1}^{m=M} \mathbf{x}^{(m)}\left(\mathbf{x}^{(m)}\right)^{T}] - \frac{\Bbb ...
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284 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, ...
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159 views

What do “$i$-th basic network”, “quantum multiplexers” and “quantum parallelism” mean in this context? How are they beneficial?

I have been reading the paper A quantum-implementable neural network model (Chen et al., 2017) for a few days now, but failed to understand how exactly their algorithm offers a speedup over the ...
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1answer
88 views

How did the authors manage to simulate and get the error estimate for a neural network with greater than 7840 qubits?

In the paper A quantum-implementable neural network model (Chen, Wang & Charbon, 2017), on page 18 they mention that "There are 784 qurons in the input layer, where each quron is comprised of ten ...
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1answer
123 views

What are some of the interesting problems whose solutions have been proposed using quantum neural networks?

I know there are some "quantum versions" of hand-writing recognition algorithms which have been proposed using quantum neural networks. Example: "Recognition of handwritten numerals by Quantum Neural ...
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Devising “structured initial guesses” for random parametrized quantum circuits to avoid getting stuck in a flat plateau

The recent McClean et al. paper Barren plateaus in quantum neural network training landscapes shows that for a wide class of reasonable parameterized quantum circuits, the probability that the ...
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278 views

Can quantum computing provide advantages related to Hardware-Neural Networks?

The following question is related to this one: Will deep learning neural networks run on quantum computers?. I found it complementary and necessary because the previous answers are not completely ...
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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 ...