Kumar, Ashwini (2021) Classifications by Artificial Neural Network (ANN) and Variational Quantum Classifier. Masters thesis, Indian Institute of Science Education and Research Kolkata.
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Text (MS Dissertation of Ashwini Kumar (16MS114))
16MS114_Thesis_file.pdf - Submitted Version Restricted to Repository staff only Download (1MB) |
Abstract
In this MS project report I have performed 4 different classifications using Artificial Neural Networks (ANNs) and Variational Quantum Classifiers (VQCs). I then com- pare their efficiency on the basis of number of parameters used for classification. The first two tasks have been inspired from earlier works done by other authors in this field. Here I have also compared the accuracy and efficiency of my models for first two tasks with the previous works of the authors. Here my aim was to show that variational quantum classifiers can classify using less number of parameters, compared to artificial neural networks. I was able to prove this for 3 out of 4 tasks, and 1 was a draw between ANN and VQC.
Item Type: | Thesis (Masters) |
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Additional Information: | Supervisor: Prof. Prasanta K. Panigrahi |
Uncontrolled Keywords: | Artificial Neural Network, Variational Quantum Classifier, ANN, VQC,comparison, classification, classifier, parameters, efficiency. |
Subjects: | Q Science > QC Physics |
Divisions: | Department of Physical Sciences |
Depositing User: | IISER Kolkata Librarian |
Date Deposited: | 08 Oct 2025 09:23 |
Last Modified: | 08 Oct 2025 09:27 |
URI: | http://eprints.iiserkol.ac.in/id/eprint/1831 |
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