{"title":"利用人工智能辅助自动化加速科学发现","authors":"Tapio Schneider, Ilkay Altintas, Daniel Atkins","doi":"10.1109/mcse.2024.3352451","DOIUrl":null,"url":null,"abstract":"AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":"39 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accelerating Scientific Discovery With AI-Aided Automation\",\"authors\":\"Tapio Schneider, Ilkay Altintas, Daniel Atkins\",\"doi\":\"10.1109/mcse.2024.3352451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.\",\"PeriodicalId\":10553,\"journal\":{\"name\":\"Computing in Science & Engineering\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computing in Science & Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/mcse.2024.3352451\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing in Science & Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/mcse.2024.3352451","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Accelerating Scientific Discovery With AI-Aided Automation
AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.
期刊介绍：
Physics, medicine, astronomy -- these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering presents scientific and computational contributions in a clear and accessible format.
The computational and data-centric problems faced by scientists and engineers transcend disciplines. There is a need to share knowledge of algorithms, software, and architectures, and to transmit lessons-learned to a broad scientific audience. CiSE is a cross-disciplinary, international publication that meets this need by presenting contributions of high interest and educational value from a variety of fields, including—but not limited to—physics, biology, chemistry, and astronomy. CiSE emphasizes innovative applications in advanced computing, simulation, and analytics, among other cutting-edge techniques. CiSE publishes peer-reviewed research articles, and also runs departments spanning news and analyses, topical reviews, tutorials, case studies, and more.
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