qsvm

Quantum Support Vector Machine (QSVM) Template supporting the Google TensorFlow and PyTorch packages.

Covalent tutorial for Q-Site conference 2022

Using Quantum Machine Learning to enhance Classification and Regression Machine Learning Models

Оптимизация дорожного трафика на графе городских улиц с использованием квантово‑вдохновлённых методов

Testing on the published article "Cross-Framework Benchmarking of Quantum Support Vector Machines on MNIST"

Real-time network log analytics pipeline for lateral movement detection using Kafka, MongoDB, FastAPI, React, and comparative ML (XGBoost, Random Forest, SVM, Isolation Forest, Autoencoders, ECOD & QSVM).

Quantum Support Vector Machine (QSVM) 6 qubit - Dataset: Bank Account Fraud

Biometric Security System Powered by QRNG QFT QSVM Architecture

Comparative study of quantum (QSVM, VQC), hybrid and classical models for physiological stress classification on WESAD and DREAMER, with subject-independent evaluation. Research in progress.

Qiskit Fall Fest Kolkata Chapter Hackathon 2022 Project on QML

Exploring Quantum Computing for Threat Detection and Intelligence on Cloud and On-Premise Infrastructure in Real Time

🔬 Quantum Machine Learning-based Credit Card Fraud Detection using Qiskit QSVM with Quantum Kernels, deployed as a Flask web application for real-time fraud prediction.

Classical vs quantum ML (QSVM, VQC in PennyLane) for financial news sentiment, benchmarked under one protocol on Financial PhraseBank

This project aims to implement Quantum Support Vector Machines (QSVM) on actual quantum devices and simulators using the Qiskit library in conjunction with Amazon Braket (AWS). The core objective is to evaluate and compare the performance efficiency of QSVM implementations across various quantum hardware and simulation environments.

Implementation of a Quantum Support Vector Machine (QSVM) focused on detecting anomalies and fraudulent patterns in financial systems. The model utilizes a quantum feature map induced by the evolution of an Ising Hamiltonian to evaluate complex and non-convex decision topologies. The simulation backend is built with Qiskit

Hybrid-Forecasting-and-Trend-Detection-of-Sea-Level-Rise

Detecting financial fraud using Quantum Support Vector Machines (QSVM). Built with Python, Qiskit, and Scikit-Learn to explore hybrid quantum-classical finance algorithms.

Empirical comparison of Quantum vs Classical SVMs on credit risk data (University Project)

Benchmark hybrid quantum-classical ML (VQC, QSVM) vs classical baselines on financial fraud detection

Benchmarking classical, graph, and quantum machine learning models for molecular property prediction on BACE, BBBP, and ClinTox.