题目:Quantum Machine Learning and its applications 时间:2022年3月17日(周四)16:00 主办方:Intelligent Computing 报告人简介: 俞上,男,之江实验室量子传感研究中心博士后。2020年于中国科学技术大学获博士学位,长期从事量子计算、量子模拟领域的实验研究,获得2018年度博士研究生国家奖学金,2020年度中科院院长奖。研究...
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Quantum Machine Learning is a novel field that merges classical Machine Learning with Quantum Information Processing, leveraging quantum computing principles like superposition and entanglement to address challenges in traditional machine learning, such as data volume and computational efficiency. ...
Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of freedom of...
Machine learning applications for noisyintermediate-scale quantum computersBrian CoyleTHEUNIVERSITYOFEDINBURGHDoctor of PhilosophyLaboratory for Foundations of Computer ScienceSchool of InformaticsUniversity of Edinburgh2022arXiv:2205.09414v1 [quant-ph] 19 May 2022 ...
Quantum mechanicsMachine learningNeural networksDrug discoveryEnergy materialsIndustrial applicationsAtomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications....
《Entanglement-Based Quantum Machine Learning》 介绍:应对大数据时代,量子机器学习的第一个实验 paper 下载 《How a Math Genius Hacked OkCupid to Find True Love》 介绍:Wired杂志报道了UCLA数学博士Chris McKinlay (图1)通过大数据手段+机器学习方法破解婚恋网站配对算法找到真爱的故事,通过Python脚本控制着12...
Outline future directions and open research questions in this rapidly evolving field. In this review, we aim to provide a comprehensive understanding of the principles, techniques and emerging applications of the integration of quantum computing and machine learning. We discuss the current state of res...
a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications. ...
At the intersection of machine learning and quantum computing, quantum machine learning has the potential of accelerating data analysis, especially for quantum data, with applications for quantum materials, biochemistry and high-energy physics. Neverthel