<p>There's already a discipline called <strong>quantum machine learning</strong>.</p>
<p>The paper <a href="https://www.nature.com/articles/s43588-022-00311-3" rel="nofollow noreferrer">Challenges and opportunities in quantum machine learning</a> focuses on quantum neural networks and quantum deep learning (according to the abstract), but feel free to look for other resources.</p>

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2024-06-15T02:16:53.760Z
2024-06-15T02:23:07.247Z
2024-06-15T02:23:07.247Z
nbro
<p>Given that qubits can exist in a superposition, meaning a qubit can represent probabilities of every possible state, what if we leverage this idea in artificial neural networks? Specifically, in scenarios where we require a softmax layer for multi-class classification, could we use the power of qubits in the output layer to reduce the number of nodes required to measure the probabilities of a prediction belonging to a particular class?</p>

<neural-networks><quantum-computing>
Can we use the capabilities of quantum computing to enhance neural networks?
Harshal Malani
# Can we use the capabilities of quantum computing to enhance neural networks?

(Asked by: username_0 on 2024-06-09)

Given that qubits can exist in a superposition, meaning a qubit can represent probabilities of every possible state, what if we leverage this idea in artificial neural networks? Specifically, in scenarios where we require a softmax layer for multi-class classification, could we use the power of qubits in the output layer to reduce the number of nodes required to measure the probabilities of a prediction belonging to a particular class?

**Tags:** neural-networks, quantum-computing


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## 1 answers

### Answer by username_1 on 2024-06-15. Score: 0 | Accepted answer

There's already a discipline called **quantum machine learning**.

The paper [Challenges and opportunities in quantum machine learning](https://www.nature.com/articles/s43588-022-00311-3) focuses on quantum neural networks and quantum deep learning (according to the abstract), but feel free to look for other resources.


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