PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
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Updated
May 13, 2024 - Python
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
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.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
Curated list of awesome papers and resources in quantum machine learning
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.
An extensive library of AI resources including books, courses, papers, guides, articles, tutorials, notebooks, AI field advancements and more.
Tensor network based quantum software framework for the NISQ era
Quantum Machine Learning Community Course
The Classiq Library is the largest collection of quantum algorithms, applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
This is the repository for https://quantumalgorithms.org
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".
QuantumFlow: A Quantum Algorithms Development Toolkit
A curated implementation of quantum algorithms with Yao.jl
QHack—The one-of-a-kind quantum computing hackathon
IEEE ICASSP 21 - Quantum Convolution Neural Networks for Speech Processing and Automatic Speech Recognition
Codes for efficiently implementing quantum neural network classifiers
A differentiable bridge between phase space and Fock space
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