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检索条件"机构=Department of Data Analysis and Machine Learning"
160 条 记 录,以下是121-130 订阅
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Ndmfcs: An Automatic Fruit Counting System in Modern Apple Orchard Using Abatement of Abnormal Fruit Detection
SSRN
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SSRN 2023年
作者: Wu, Zhenchao Sun, Xiaoming Jiang, Hanhui Mao, Wulan Li, Rui Andriyanov, Nikita Soloviev, Vladimir Fu, Longsheng College of Mechanical and Electronic Engineering Northwest A&F University Shaanxi Yangling712100 China Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs Shaanxi Yangling712100 China Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service Shaanxi Yangling712100 China Northwest A&F University Shenzhen Research Institute Guangdong Shenzhen518000 China Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Moscow125167 Russia Institute of Agricultural Mechanization Xinjiang Academy of Agricultural Sciences Urumqi830000 China
Automatic fruit counting is an important task for growers to estimate yield and manage orchards. Although many deep-learning-based fruit detection algorithms have been developed to improve performance of automatic fru... 详细信息
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Neural networks and their application in forecasting problems
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Journal of Physics: Conference Series 2020年 第1期1703卷
作者: V A Ivanyuk F F Pashchenko Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation 49 Leningradsky Prospekt 125993 Moscow Russia Department of Higher Mathematics Bauman Moscow State Technical University Moscow Russia V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia
The report describes popular machine learning methods and applications of neural networks. It reveals methods of training neural networks and offers a method of forecasting based on neural networks for modelling finan...
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Forecasting the dynamics of financial time series based on neural networks
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Journal of Physics: Conference Series 2020年 第1期1703卷
作者: V A Ivanyuk N M Abdikeev A D Tsvirkun Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation 49 Leningradsky Prospekt 125993 Moscow Russia Department of Higher Mathematics Bauman Moscow State Technical University Moscow Russia V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia
Forecasting is one of the high-demand data mining problems, but also a very difficult one. The difficulties of forecasting are associated with insufficient quality and quantity of input data, the changes in the enviro...
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Ensemble forecasting method
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Journal of Physics: Conference Series 2020年 第1期1703卷
作者: V A Ivanyuk A D Tsvirkun Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation 49 Leningradsky Prospekt 125993 Moscow Russia Department of Higher Mathematics Bauman Moscow State Technical University Moscow Russia V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia
The purpose of this article is to analyze the time series based on aggregate forecasting methods. Forecasting time series comprises an important scientific and technical task which is relevant in various sectors of ec...
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AstroPhot: Fitting Everything Everywhere All at Once in Astronomical Images
arXiv
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arXiv 2023年
作者: Stone, Connor J. Courteau, Stéphane Cuillandre, Jean-Charles Hezaveh, Yashar Perreault-Levasseur, Laurence Arora, Nikhil Department of Physics Université de Montréal MontréalQC Canada Mila - Québec Artificial Intelligence Institute MontréalQC Canada Ciela - Montréal Institute for Astrophysical Data Analysis and Machine Learning MontréalQC Canada Department of Physics Engineering Physics & Astronomy Queen’s University KingstonON Canada AIM CEA CNRS Université Paris-Saclay Université de Paris Gif-sur-YvetteF-91191 France Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States New York University Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates New York University Abu Dhabi United Arab Emirates
We present ASTROPHOT, a fast, powerful, and user-friendly Python based astronomical image photometry solver. ASTROPHOT incorporates automatic differentiation and GPU (or parallel CPU) acceleration, powered by the mach... 详细信息
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The Cosmic Microwave Background and H0
arXiv
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arXiv 2023年
作者: Lemos, Pablo Shah, Paul Mila - Quebec Artificial Intelligence Institute Montréal 6666 Rue Saint-Urbain QCH2S 3H1 Canada Department of Physics Université de Montréal Montréal 1375 Avenue Thérèse-Lavoie-Roux QCH2V 0B3 Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom
The cosmic microwave background (CMB) offers a unique window into the earlyuniverse, providing insights into cosmological parameters like the Hubbleconstant. Recent precise measurements of the CMB by experiments like ... 详细信息
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The dark balance: quantifying the inner halo response to active galactic nuclei feedback in galaxies
arXiv
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arXiv 2024年
作者: Arora, Nikhil Courteau, Stéphane Macciò, Andrea V. Cho, Changhyun Patel, Raj Stone, Connor New York University Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates New York University Abu Dhabi Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates Department of Physics Engineering Physics & Astronomy Queen’s University KingstonONK7L 3N6 Canada Max-Planck-Institut für Astronomie Königstuhl 17 HeidelbergD-69117 Germany Department of Physics Université de Montréal MontréalQC Canada Mila - Québec Artificial Intelligence Institute MontréalQC Canada Ciela - Montréal Institute for Astrophysical Data Analysis and Machine Learning MontréalQC Canada
This paper presents a study of the impact of supermassive black hole (SMBH) feedback on dark matter (DM) halos in numerical NIHAO simulations of galaxies. In particular, the amount of DM displaced via active galactic ... 详细信息
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Posterior Sampling of the Initial Conditions of the Universe from Non-linear Large Scale Structures using Score-Based Generative Models
arXiv
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arXiv 2023年
作者: Legin, Ronan Ho, Matthew Lemos, Pablo Perreault-Levasseur, Laurence Ho, Shirley Hezaveh, Yashar Wandelt, Benjamin Department of Physics Université de Montréal Montréal Canada Mila - Quebec Artificial Intelligence Institute Montréal Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Sorbonne Université CNRS UMR 7095 Institut d’Astrophysique de Paris 98 bis bd Arago Paris75014 France Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Sorbonne Université Institut Lagrange de Paris 98 bis boulevard Arago Paris75014 France
Reconstructing the initial conditions of the universe is a key problem in cosmology. Methods based on simulating the forward evolution of the universe have provided a way to infer initial conditions consistent with pr... 详细信息
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Simulation-guided galaxy evolution inference: A case study with strong lensing galaxies
arXiv
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arXiv 2023年
作者: Filipp, Andreas Shu, Yiping Pakmor, Rüdiger Suyu, Sherry H. Huang, Xiaosheng Technical University Munich TUM School of Natural Sciences Physics Department James-Franck-Strasse 1 Garching85748 Germany Karl-Schwarzschlid-Strasse 1 Garching85748 Germany Université de Montréal Physics Department 1375 Ave.Thérèse-Lavoie-Roux MontréalQCH2V 0B3 Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Mila - Quebec Artificial Intelligence Institute Montréal Canada Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China 11F of ASMAB No.1 Section 4 Roosevelt Road Taipei10617 Taiwan University of San Francisco 2130 Fulton Street San FranciscoCA94117-1080 United States
Understanding the evolution of galaxies provides crucial insights into a broad range of aspects in astrophysics, including structure formation and growth, the nature of dark energy and dark matter, baryonic physics, a... 详细信息
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Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
arXiv
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arXiv 2024年
作者: Bassi, Pedro R.A.S. Li, Wenxuan Tang, Yucheng Isensee, Fabian Wang, Zifu Chen, Jieneng Chou, Yu-Cheng Roy, Saikat Kirchhoff, Yannick Rokuss, Maximilian Huang, Ziyan Ye, Jin He, Junjun Wald, Tassilo Ulrich, Constantin Baumgartner, Michael Maier-Hein, Klaus H. Jaeger, Paul Ye, Yiwen Xie, Yutong Zhang, Jianpeng Chen, Ziyang Xia, Yong Xing, Zhaohu Zhu, Lei Sadegheih, Yousef Bozorgpour, Afshin Kumari, Pratibha Azad, Reza Merhof, Dorit Shi, Pengcheng Ma, Ting Du, Yuxin Bai, Fan Huang, Tiejun Zhao, Bo Wang, Haonan Li, Xiaomeng Gu, Hanxue Dong, Haoyu Yang, Jichen Mazurowski, Maciej A. Gupta, Saumya Wu, Linshan Zhuang, Jiaxin Chen, Hao Roth, Holger Xu, Daguang Blaschko, Matthew B. Decherchi, Sergio Cavalli, Andrea Yuille, Alan L. Zhou, Zongwei Department of Computer Science Johns Hopkins University United States Department of Pharmacy and Biotechnology University of Bologna Italy Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Italy NVIDIA United States Germany Germany ESAT-PSI KU Leuven Belgium Faculty of Mathematics and Computer Science Heidelberg University Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Germany Shanghai Jiao Tong University China Shanghai Artificial Intelligence Laboratory China Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany DKFZ Germany School of Computer Science and Engineering Northwestern Polytechnical University China Australian Institute for Machine Learning The University of Adelaide Australia College of Computer Science and Technology Zhejiang University China Hong Kong University of Science and Technology Guangzhou China Hong Kong University of Science and Technology Hong Kong Faculty of Informatics and Data Science University of Regensburg Germany Faculty of Electrical Engineering and Information Technology RWTH Aachen University Germany Fraunhofer Institute for Digital Medicine MEVIS Germany Electronic & Information Engineering School Harbin Institute of Technology Shenzhen China China The Chinese University of Hong Kong Hong Kong Peking University China Department of Electrical and Computer Engineering Duke University United States Stony Brook University United States Department of Computer Science and Engineering Department of Chemical and Biological Engineering Division of Life Science Hong Kong University of Science and Technology Hong Kong Data Science and Computation Facility Fondazione Istituto Italiano di Tecnologia Italy Ecole Polytechnique Fédérale de Lausanne Switzerland
How can we test AI performance? This question seems trivial, but it isn’t. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and sho... 详细信息
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