variational-quantum-circuits

Курс по квантовому машинному обучению

Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.

Fairness-aware, explainable AutoML for quantum + classical ML — 21 models, one Optuna search, SHAP & AI reports. uvx quoptuna

Qiskit implementation of classical shadow formalism with VQE for calculating ground state energies of molecules

Simulate and optimize quantum communication networks using quantum computers.

Variational Quantum Algorithms for Unsupervised Image Segmentation

QuACS: Variational Quantum Algorithm for Coalition Structure Generation in Induced Subgraph Games

Comparative study: Quantum vs. classical models for Cart Pole. Examining entanglement layers and data re-uploading, highlighting quantum model superiority.

When performance survives noise, identifiability may not.

Verification harness for quantum ML. A reproducible lab for stress-testing quantum models where predictive accuracy, identifiability, curvature, and robustness under noise can diverge.

This repository contains the source code and results for the experiments presented in Evaluating Parameter-Based Training Performance of Neural Networks and Variational Quantum Circuits.

Hierarchical federated quantum machine learning benchmark for communication-efficient smart-city sensing over 6G (IEEE GLOBECOM 2026 WS-02)

An advanced exploration of Quantum Fourier Transform (QFT) using Quantum Machine Learning (QML). This project delves into the optimization of variational quantum circuits, leveraging machine learning techniques to evaluate and visualize the transformation capabilities of QFT in quantum computing.

Hybrid quantum-classical neural network for passive OS fingerprinting — 20-qubit PennyLane variational circuit with a PyTorch head, trained on nPrint packet features

A demonstration of using variational quantum optimization (VQO) to find a quantum protocol that maximally violates the CHSH inequality.

Companion notebook for A Technical Introduction to Quantum Neural Networks. Four small PennyLane experiments on encoding, depth and trainability, classical baselines, and finite-shot cost.

The code for the article "Certified variational quantum algorithms for eigenstate preparation"

Framework di ricerca per la generazione di dati sintetici tabulari equi e interpretabili tramite Variational Quantum Circuits (VQC). Integra vincoli di fairness nel circuito, stima la purezza con qsalto (Bell sampling) e spiega il contributo causale delle porte quantistiche mediante Quantum Shapley Values (SVQX).

Planting a clinical dependency graph into the entanglement topology of a shallow quantum circuit, to generate synthetic MIMIC-IV ICU data. A light-cone theorem forces the circuit to be shallow, and makes the graph's alignment measurable.

Hybrid Quantum-Classical Brain Tumor Detection using ResNet50, VQC, Grad-CAM, and Integrated Gradients for Explainable AI in Medical Imaging.