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...
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 is a branch of artificial intelligence that is being used at a large scale to solve science, engineering, and medical tasks. Quantum computing is an emerging technology that has a very high computational ability to solve complex problems. Classical machine learning ...
Meanwhile, rapid progress has been made in the field of quantum computation including developing both powerful quantum algorithms and advanced quantum devices. The interplay between machine learning and quantum physics holds the intriguing potential for bringing practical applications to the modern society. ...
machine learningQuantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information, quantum gravity, and large-scale numerical ...
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....
Machine-learning force fields (MLFF) should be accurate, computationally and\ndata efficient, and applicable to molecules, materials, and interfaces thereo... HE Sauceda,LE Gálvez-González,S Chmiela,... 被引量: 0发表: 2021年 BIGDML—Towards accurate quantum machine learning force fields for...
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
第3章《统计物理与机器学习》(Statistical Physics and Machine Learning) 探讨了统计物理学的概念和方法如何应用于机器学习领域。以下是该章节的主要内容概述: ### 3.1 引言 (Introduction) - 介绍了统计物理学与机器学习之间的联系,并讨论了这种跨学科合作的潜在价值。
Data-driven approaches are currently renovating the field of heterogenous catalysis and open the door to advance catalyst design. Their success depends heavily on the synergy among machine learning (ML), experimental data, and quantum mechanical (QM) calculations. In this brief survey of recent progr...