Questions tagged [machine-learning]
For questions about how quantum computing could improve or affect machine learning i.e. quantum machine learning. Questions about classical machine learning belong on another site, such as Stack Overflow, Cross Validated or Artificial Intelligence SE.
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Training Quantum circuits in QML [closed]
I have 100 quantum circuits stored in a list, with rotational gates as parameter vector, now I need to train these circuits. As of I saw qikit has code only for training classical dataset values. ...
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Building QRNN Model Using Qiskit
I'm trying to build a QRNN model as described in this paper (arxiv). The code that I have been able to design so far is as follows:
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Implementing stochastic gradient descent on hybrid quantum-classical optimization
I am working on a project in which I need to simulate the paper https://arxiv.org/abs/1910.01155.
So I am a complete beginner to qiskit but I read its documentation so I know some stuff. So basically ...
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Is there any machine learning method for finding quantum error correction codes?
To define a quantum error correction code, first one needs to model noise, such as Pauli noise, dephasing noise, etc.
Then according to the noise, look for the code space, stabilizer, and logical ...
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Qiskit VQC - how does VQC associate the measurement results with labels?
I'm working through the example here, and am struggling to see at what stage it is specified how the measurement results/ or expectations collected from the circuit are used to decide which label to ...
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Implementation of identity block initialisation strategy for mitigating barren plateaus
I have been trying to implement this paper on identity block initialisation strategy for barren plateau mitigation but I don't really understand how one would apply it to a parameterised circuit with ...
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Gradient-free optimization in Qiskit without using pre-defined classes
Basically I want to build a gradient-free optimizer that classifies a very simple dataset (e.g. the sklearn make_moons) using scipy.optimize (Nelder-Mead or Powell ...
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Quantum data as input for Quantum Neural Net
I'm new to quantum machine learning, and I wanted to know how quantum data is processed in a quantum neural net.
For example, if I am training a QNN to classify entangled circuits from non-entangled ...
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Quantum Convolutional Neural Network not producing gradients
I am trying to bulid a quantum convolutional neural network for image classification with Pennylane and Keras but the model isn't training and I keep getting the warning:
WARNING:tensorflow:Gradients ...
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Resources on quantum machine learning for beginners
I am a first year PhD Physics student, working on quantum information theory. I am planning to learn machine learning and in particular quantum machine learning. I do not have any prior exposure to ...
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Is QST a inherently supervised or unsupervised problem in Machine Learning?
I am studying how to apply neural networks to the problem of Quantum State Tomography and I got confused when it comes to decide if this is a supervised or unsupervised learning problem.
At first, I ...
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Turn expectation values back into classical data
How are expectation values turned back into classical data for evaluation?
I have a circuit performing a regression task that returns the expectation value of the Pauli Z operator. I would like to ...
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Transform QLSTM model output expectation values back into classical data
What is the typical procedure for transforming a model's expvals back into the classical data format? I'm new to QML and need some insight.
I have some expvals that were the output of model i.e. ...
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Qnode model gradient of inputs (not parameters!) question
I am trying to use qml to do physics informed quantum machine learning within Tensorflow. I know with TF, to get derivatives of the network's inputs (df/dx, for example), you can use with tf....
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Quantum neural networks and quantum kernels deal with nonlinearities
I'm trying to understand quantum neural networks from reading Alchieri et al.'s review paper. The following paragraph describes the differences between classical and quantum neural networks:
Also, ...
