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检索条件"机构=Department of Computer Science and Program in Statistical and Data Sciences"
297 条 记 录,以下是71-80 订阅
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Empowering Biomedical Discovery with AI Agents
arXiv
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arXiv 2024年
作者: Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States
We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimenta... 详细信息
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Network Intrusion Detection System Using Principal Component Analysis Algorithm and Decision Tree Classifier
Network Intrusion Detection System Using Principal Component...
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International Conference on Computational science and Computational Intelligence (CSCI)
作者: Oyeyemi Osho Sungbum Hong Tor A. Kwembe Department of Computational Data-Enabled Science and Engineering(CDS&#x0026 E) Jackson State University Jackson MS USA Department of Electrical &#x0026 Computer Engineering and Computer Science Jackson State University Jackson MS USA Department of Mathematics &#x0026 Statistical Sciences Jackson State University Jackson MS USA
Network Intrusion Detection Systems (IDS) have become expedient for network security and ensures the safety of all connected devices. Network Intrusion Detection System (IDS) alludes to observing network data informat... 详细信息
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Streamlines in the Two-Dimensional Spreading of a Thin Fluid Film: Blowing and Suction Velocity Proportional to the Height
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Journal of Applied Mathematics and Physics 2021年 第11期9卷 2114-2151页
作者: N. Modhien D. P. Mason E. Momoniat School of Computer Science and Applied Mathematics DST-NRF Centre of Excellence in Mathematical and Statistical Sciences University of the Witwatersrand Johannesburg South Africa Data Science across Disciplines Research Group Institute for the Future of Knowledge University of Johannesburg and Department of Mathematics and Applied Mathematics University of Johannesburg Johannesburg South Africa
The two-dimensional spreading under gravity of a thin fluid film with suction (fluid leak-off) or blowing (fluid injection) at the base is considered. The thin fluid film approximation is imposed. The height of the th... 详细信息
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Unbiased Estimation Using a Class of Diffusion Processes
SSRN
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SSRN 2022年
作者: Ruzayqat, Hamza Beskos, Alexandros Crisan, Dan Jasra, Ajay Kantas, Nikolas Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Statistical Science University College London LondonWC1E 6BT United Kingdom Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom
We study the problem of unbiased estimation of expectations with respect to (w.r.t.) π a given, general probability measure on (Rd,B(Rd)) that is absolutely continuous with respect to a standard Gaussian measure. We ... 详细信息
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Parameter estimation and uncertainty quantification using information geometry
arXiv
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arXiv 2021年
作者: Sharp, Jesse A. Browning, Alexander P. Burrage, Kevin Simpson, Matthew J. School of Mathematical Sciences Queensland University of Technology Brisbane Australia ARC Centre of Excellence for Mathematical and Statistical Frontiers QUT Australia Department of Computer Science University of Oxford Oxford United Kingdom QUT Centre for Data Science QUT Australia
In this work we: (1) review likelihood-based inference for parameter estimation and the construction of confidence regions;and, (2) explore the use of techniques from information geometry, including geodesic curves an... 详细信息
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CONCENTRATION INEQUALITIES AND OPTIMAL NUMBER OF LAYERS FOR STOCHASTIC DEEP NEURAL NETWORKS
arXiv
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arXiv 2022年
作者: Caprio, Michele Mukherjee, Sayan PRECISE Center Department of Computer and Information Science University of Pennsylvania 3330 Walnut Street PhiladelphiaPA19104 United States Center for Scalable Data Analytics and Artificial Intelligence Universität Leipzig Humboldtstraße 25 Leipzig04105 Germany The Max Planck Institute for Mathematics in the Sciences Inselstraße 22 Leipzig04103 Germany Departments of Statistical Science Mathematics Computer Science and Biostatistics & Bioinformatics Duke University DurhamNC27708 United States
We state concentration inequalities for the output of the hidden layers of a stochastic deep neural network (SDNN), as well as for the output of the whole SDNN. These results allow us to introduce an expected classifi... 详细信息
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Unbiased Estimation using a Class of Diffusion Processes
arXiv
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arXiv 2022年
作者: Ruzayqat, Hamza Beskos, Alexandros Crisan, Dan Jasra, Ajay Kantas, Nikolas Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 KSA Saudi Arabia Department of Statistical Science University College London LondonWC1E 6BT United Kingdom Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom
We study the problem of unbiased estimation of expectations with respect to (w.r.t.) π a given, general probability measure on (d, B(d)) that is absolutely continuous with respect to a standard Gaussian measure. We f... 详细信息
来源: 评论
SCALE RELIANT INFERENCE
arXiv
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arXiv 2022年
作者: Nixon, Michelle Pistner McGovern, Kyle C. Letourneau, Jeffrey David, Lawrence A. Lazar, Nicole A. Mukherjee, Sayan Silverman, Justin D. College of Information Sciences and Technology The Pennsylvania State University United States Program in Bioinformatics and Genomics The Pennsylvania State University United States Department of Molecular Genetics and Microbiology Duke University United States Department of Statistics The Pennsylvania State University United States Huck Institutes for the Life Sciences The Pennsylvania State University United States Departments of Statistical Science Mathematics Computer Science Biostatistics & Bioinformatics Duke University United States Center for Scalable Data Analytics and Artificial Intelligence University of Leipzig Germany Max Planck Institute for Mathematics in the Natural Sciences Germany Department of Medicine The Pennsylvania State University United States
Many scientific fields, including human gut microbiome science, collect multivariate count data where the sum of the counts is unrelated to the scale of the underlying system being measured (e.g., total microbial load... 详细信息
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GLOBAL OPTIMALITY OF ELMAN-TYPE RNNS IN THE MEAN-FIELD REGIME
arXiv
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arXiv 2023年
作者: Agazzi, Andrea Lu, Jianfeng Mukherjee, Sayan Department of Mathematics Università Di Pisa Pisa Italy Department of Mathematics Duke University DurhamNC27708 United States Department of Physics Duke University DurhamNC27708 United States Department of Chemistry Duke University DurhamNC27708 United States Center for Scalable Data Analytics and Artificial Intelligence Universität Leipzig Leipzig Germany Max Planck Institute for Mathematics in the Sciences Leipzig Germany Department of Statistical Science Duke University DurhamNC27708 United States Department of Computer Science Duke University DurhamNC27708 United States Department of Biostatistics & Bioinformatics Duke University DurhamNC27708 United States
We analyze Elman-type Recurrent Reural Networks (RNNs) and their training in the mean-field regime. Specifically, we show convergence of gradient descent training dynamics of the RNN to the corresponding mean-field fo... 详细信息
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Precision Rehabilitation for Patients Post-Stroke based on Electronic Health Records and Machine Learning
arXiv
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arXiv 2024年
作者: Gao, Fengyi Zhang, Xingyu Sivarajkumar, Sonish Denny, Parker E. Aldhahwani, Bayan M. Visweswaran, Shyam Shi, Ryan Hogan, William Bove, Allyn Wang, Yanshan Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Communication Science and Disorders University of Pittsburgh PittsburghPA United States Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Physical Therapy University of Pittsburgh PittsburghPA United States Department of Medical Rehabilitation Sciences Umm Al-Qura University Makkah Saudi Arabia Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Department of Computer Science University of Pittsburgh Medical Center PittsburghPA United States Data Science Institute Medical College of Wisconsin MilwaukeeWI United States Hillman Cancer Center University of Pittsburgh Medical Center PittsburghPA United States
Objective In this study, we utilized statistical analysis and machine learning methods to examine whether rehabilitation exercises can improve patients post-stroke functional abilities, as well as forecast the improve... 详细信息
来源: 评论