Trending repositories for topic quantum-machine-learning
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 computer...
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
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 computer...
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. 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 computer...
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
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 🙌
An open-source Python framework for hybrid quantum-classical machine learning.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
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 computer...
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 🙌
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
An open-source Python framework for hybrid quantum-classical machine learning.
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
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 computer...
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 🙌
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Tensor network based quantum software framework for the NISQ era
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
Curated list of awesome papers and resources in quantum machine learning
Quantum-classical hybrid convolutional neural network for classical image classification
A curated list of recent textbooks, reviews, perspectives, and research papers related to quantum machine learning, variational quantum algorithms, tensor networks, and classical machine learning appl...
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
IEEE ICASSP 21 - Quantum Convolution Neural Networks for Speech Processing and Automatic Speech Recognition
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
Tensor network based quantum software framework for the NISQ era
Quantum-classical hybrid convolutional neural network for classical image classification
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
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 computer...
A curated list of recent textbooks, reviews, perspectives, and research papers related to quantum machine learning, variational quantum algorithms, tensor networks, and classical machine learning appl...
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
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 🙌
IEEE ICASSP 21 - Quantum Convolution Neural Networks for Speech Processing and Automatic Speech Recognition
Curated list of awesome papers and resources in quantum machine learning
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
QuAIRKit is a Python research framework for quantum computing, quantum information, and quantum machine learning algorithm development. It focuses on flexible design, real-time simulation and rapid ve...
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 🙌
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
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 computer...
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
An open-source Python framework for hybrid quantum-classical machine learning.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
Tensor network based quantum software framework for the NISQ era
Quantum-classical hybrid convolutional neural network for classical image classification
piQture: A quantum machine learning library for image processing.
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
An extensive library of AI resources including books, courses, papers, guides, articles, tutorials, notebooks, AI field advancements and more.
Curated list of awesome papers and resources in quantum machine learning
QuAIRKit is a Python research framework for quantum computing, quantum information, and quantum machine learning algorithm development. It focuses on flexible design, real-time simulation and rapid ve...
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 🙌
This repository consists of documentation regarding quantum machine learning (QML), covering both beginner's guides and advanced topics.
Quantum-classical hybrid convolutional neural network for classical image classification
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
Official code for the paper "Predicting Properties of Quantum Systems with Conditional Generative Models"
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Tensor network based quantum software framework for the NISQ era
修改谷歌提供的样例量子卷积神经网络模型，基于KDD99数据集进行训练，实现了网络攻击分类检测。
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 computer...
Qiskit Hackathon Korea 2021 Community Choice Award Winner : Exploring Hybrid quantum-classical Neural Networks with PyTorch and Qiskit
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.