Quantum-Machine-Learning/CITATION.cff at main · rasidi3112/Quantum-Machine-Learning · GitHub

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cff-version: 1.2.0
title: "Quantum Machine Learning: Hybrid VQC vs Quantum Kernel SVM"
message: "Jika Anda menggunakan kode ini, mohon sertakan kutipan berikut."
authors:
  - family-names: "Rasidi"
    given-names: "Ahmad"
    email: "rasidi.basit@gmail.com"
    affiliation: "Independent Researcher — Quantum Computing and Machine Learning"
abstract: >
  This repository presents a comparative experimental study of hybrid quantum-classical learning
  models using PennyLane, PyTorch, and Qiskit.
  It implements both Variational Quantum Classifier (VQC) and Quantum Kernel SVM (QSVM) architectures
  for binary classification tasks, highlighting differences in performance and design between
  variational and kernel-based quantum models.

  The project follows international research standards for reproducibility, modular configuration,
  and open scientific development.

keywords:
  - Quantum Machine Learning
  - Variational Quantum Classifier
  - Quantum Kernel SVM
  - PennyLane
  - Qiskit
  - PyTorch
  - Hybrid Quantum-Classical
  - Open Research

license: MIT
repository-code: "https://github.com/rasidi3112/Quantum-Machine-Learning"
version: "1.0.0"
date-released: 2025-10-19
preferred-citation:
  type: article
  authors:
    - family-names: "Rasidi"
      given-names: "Ahmad"
  title: "Quantum Machine Learning: Hybrid VQC vs Quantum Kernel SVM"
  journal: "Independent Quantum Computing Research Archive"
  year: 2025
  url: "https://github.com/rasidi3112/Quantum-Machine-Learning"