Quantum Machine LearningDeep LearningReal-World ApplicationsFake News DetectionQuantum AdvantageMany prevalent issues in today's society, such as fake news detection, can be efficiently addressed using artificia
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 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 ...
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
Quantum computing has become popular as a result of the rise in computational demands for solving issues in a variety of sectors that are computationally e
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
7.2Quantum reinforcement learning Because of its innovation incomputer vision, QRL has received a lot of attention. The idea of QRL is inspired by quantum computing’sstate superpositiontheory andquantum parallelism. QRL outperformsRLin terms of learning speed, which leads to a balance between exploita...
As hardware improves, hybrid quantum-classical models will become more powerful. We can expect to see breakthroughs in combining classical deep learning with quantum-enhanced optimization. 4. Commercial Applications Many companies, including IBM, Google, and Microsoft, are actively investing in quantum ...
Quantum machine learning (QML) is at the nexus of two very hyped topics: artificial intelligence and quantum computing. Ignoring the AI hype, let's explore how realistic quantum machine learning is.
reinforcement learning and quantum finance approaches applied in financial domain.Section 10illustrates comparison between traditional and ML-based approaches. InSection 11, we report the final considerations of this paper. 2. Research Methodology