quantum-machine-learning

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.

An open-source Python framework for hybrid quantum-classical machine learning.

The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌

Curated list of open-source quantum software projects.

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.

Curated list of awesome papers and resources in quantum machine learning

Tensor network based quantum software framework for the NISQ era

This repository contains the source code used to produce the results presented in the paper "Continuous-variable quantum neural networks". Due to subsequent interface upgrades, these scripts will work only with Strawberry Fields version <= 0.10.0.

Курс по квантовому машинному обучению

This is the repository for https://quantumalgorithms.org

Quantum-classical hybrid convolutional neural network for classical image classification

The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.

Tensor-Based Quantum Machine Learning

This repository contains the source code used to produce the results presented in the paper "Machine learning method for state preparation and gate synthesis on photonic quantum computers".

IEEE ICASSP 21 - Quantum Convolution Neural Networks for Speech Processing and Automatic Speech Recognition

A curated implementation of quantum algorithms with Yao.jl

QuantumFlow: A Quantum Algorithms Development Toolkit