AI代码解释 from qiskitimportAer,QuantumCircuit from qiskit_machine_learning.kernelsimportQuantumKernel from qiskit.circuitimportParameterVector # 创建一个两量子比特的量子电路,作为特征映射 feature_dimension=2x=ParameterVector('x',feature_dimension)feature_map=QuantumCircuit(feature_dimension)# 对量子比特应用Ha...
近日,来自 南洋理工大学计算与数据科学学院(NTU)、新加坡国立大学量子技术中心(CQT)、鸿海研究院(Hon Hai Research Institute) 的研究团队发布了一篇专为 AI 研究者与开发者 设计的 QML 教程,论文地址:Quantum Machine Learning: A Hands-...
近日,来自 南洋理工大学计算与数据科学学院(NTU)、新加坡国立大学量子技术中心(CQT)、鸿海研究院(Hon Hai Research Institute) 的研究团队发布了一篇专为 AI 研究者与开发者 设计的 QML 教程,论文地址:Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers(https://arxiv...
量子深度学习(quantum deep learning) 主要是指量子玻尔兹曼机(quantum Boltzmann Machine). 类似于经典的玻尔兹曼机,量子玻尔兹曼机的训练也是寻找一系列参数,来找到可以使得input training data近似满足玻尔兹曼分布(即统计物理里面的thermal分布)。量子算法相比经典算法的优势在于,更好的采样,更快的thermalize过程亦即更快的...
量子深度学习(quantum deep learning) 主要是指量子玻尔兹曼机(quantum Boltzmann Machine). 类似于经典的玻尔兹曼机,量子玻尔兹曼机的训练也是寻找一系列参数,来找到可以使得input training data近似满足玻尔兹曼分布(即统计物理里面的thermal分布)。量子算法相比经典算法的优势在于,更好的采样,更快的thermalize过程亦即更快的...
Quantum machine learning may advanceAIby speeding up training for complex models such as deep learning architectures. Innatural language processing(NLP), QML can enable more efficient parsing and understanding of human language, leading to improved AI assistants, translation systems, and chatbots. ...
包括经典机器学习算法(classical machine learning algorithms)和Quantum AI的混合模式(hybrid model),将很快带来实际应用价值。
Quantum machine learning applied to condensed matter physics is the topic of the next section. Here, successful learning of quantum datasets arises through the use of clustering and classification methods. A database with datasets optimized using the VQE algorithm is established for providers of cloud...
21 - Variational Circuits and Quantum Simulation 22-Variational Circuits and Quantum Simulation 3 (Al 23 - Variational Circuits and Quantum Simulation 24 - Encoding Classical Information 25 - Ensemble Learning 26 - QBoost 27 - Clustering by Quantum Optimization 28 - Kernel Methods 29 - An Interferen...
This book presents a new way of thinking about quantum mechanics and machine learning by merging the two. Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes clear through the density matrix operator which can be readily approximated by neural network models...