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Implement Data-reuploading classifier in Qiskit Machine Learning #668
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Signed-off-by: Shivani Rajput<[email protected]>
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The notebook needs to be updated for the unit tests:
- Check spelling
- Update outdated libraries
Hi @ShivaniRajput11, are you still interested in finishing this PR? There are just a few things left to change to make it compatible with the latest Qiskit ML version:
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Hi @edoaltamura , yes I am still interested to finish this PR. I am working on it. Thanks. |
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Note the recent changes in Qiskit ML that would require changes in this PR:
from qiskit.utils import algorithm_globals
:algorithm_globals
is now hosted in Qiskit ML directly since the merge of Qiskit Algorithm last week.- A new tutorial, number 13, has been merged in the main branch, so this tutorial should be renamed with the number 14.
- The V1 primitives are being deprecated across the Qiskit ecosystem and this change may affect
SamplerQNN
used here. Soon we will update Qiskit ML to reflect this upgrade, so this tutorial may need to be adjusted as well.
Description
Data re-uploading is a recently proposed idea of quantum neural network, which uses a quantum circuit with a series of data re-uploading and processing layers. Unlike the conventional quantum circuit of quantum neural network, it has multiple layers of re-uploading input data. In this project, we will implement the data re-uploading quantum neural network in Qiskit Machine Learning. The goal of this project is to write code and create a pull request
Details and comments
The work is done in QAMP23 (qiskit-advocate/qamp-spring-23#3)