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检索条件"机构=Department of Data Analysis and Machine Learning"
159 条 记 录,以下是121-130 订阅
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The medical algorithmic audit (vol 4, pg e384, 2022)
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LANCET DIGITAL HEALTH 2022年 第6期4卷 E405-E405页
作者: Liu, X. Glocker, B. McCradden, M. M. Ghassemi, M. Denniston, A. K. Oakden-Rayner, L. Academic Unit of Ophthalmology Institute of Inflammation and Ageing College of Medical and Dental Sciences University of Birmingham UK Department of Ophthalmology University Hospitals Birmingham NHS Foundation Trust Birmingham UK Moorfields Eye Hospital NHS Foundation Trust London UK Health Data Research UK London UK Birmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham UK Biomedical Image Analysis Group Department of Computing Imperial College London London UK The Hospital for Sick Children Toronto ON Canada Dalla Lana School of Public Health Toronto ON Canada Institute for Medical Engineering and Science and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA National Institute of Health Research Biomedical Research Centre for Ophthalmology Moorfields Hospital London NHS Foundation Trust London UK University College London Institute of Ophthalmology London UK Australian Institute for Machine Learning University of Adelaide Adelaide SA Australia. lauren.oakden-rayner@adelaide.edu.au
Artificial intelligence systems for health care, like any other medical device, have the potential to fail. However, specific qualities of artificial intelligence systems, such as the tendency to learn spurious correl...
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Efficient Algorithms for Set-Valued Prediction in Multi-Class Classification
arXiv
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arXiv 2019年
作者: Mortier, Thomas Wydmuch, Marek Dembczyński, Krzysztof Hüllermeier, Eyke Waegeman, Willem Department of Data Analysis and Mathematical Modelling Ghent University Belgium Institute of Computing Science Poznań University of Technology Poland Intelligent Systems and Machine Learning Universität Paderborn Germany
In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little guarantee. More precisely, the classifier should strive for an opt... 详细信息
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222P Artificial intelligence (AI) based prognostication from baseline computed tomography (CT) scans in a phase III advanced non-small cell lung cancer (aNSCLC) trial
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Annals of Oncology 2024年 35卷 S304-S304页
作者: O.F. Khan J. Montalt-Tordera J. Riskas S.A. Haider V. Sivan O. Samorodova J. Hennessy A. Mitchell S.S. Mohammadi E. Di Tomaso T. Banerji F. Baldauf-Lenschen C. Glaus Oncology Department Cumming School of Medicine Tom Baker Cancer Centre Calgary AB Canada Computer Vision & Sound Analysis Bayer Hispania S.L. Sant Joan Despí Spain Machine Learning Altis Labs Inc. Toronto ON Canada Radiology Altis Labs Inc. Toronto ON Canada Data Altis Labs Inc. Toronto ON Canada Biostatistics Altis Labs Inc. Toronto ON Canada Computer Vision & Sound Analysis Bayer AG Leverkusen Germany Translational Sciences Oncology Bayer U.S. LLC Cambridge MA USA Digital Lead Global Brands Bayer U.S. LLC Whippany NJ USA Executive Altis Labs Inc. Toronto ON Canada
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Field-level simulation-based inference of galaxy clustering with convolutional neural networks
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Physical Review D 2024年 第8期109卷 083536-083536页
作者: Pablo Lemos Liam Parker ChangHoon Hahn Shirley Ho Michael Eickenberg Jiamin Hou Elena Massara Chirag Modi Azadeh Moradinezhad Dizgah Bruno Régaldo-Saint Blancard David Spergel Department of Physics Université de Montréal Montréal 1375 Avenue Thérèse-Lavoie-Roux Montréal QC H2V 0B3 Canada Mila—Quebec Artificial Intelligence Institute Montréal 6666 Rue Saint-Urbain Montréal QC H2S 3H1 Canada Ciela—Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New York New York 10010 USA Department of Physics Princeton University Princeton New Jersey 08544 USA Center for Cosmology and Particle Physics Department of Physics New York University New York New York 10003 USA Department of Physics Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Center for Computational Mathematics Flatiron Institute 162 5th Avenue New York New York 10010 USA Department of Astronomy University of Florida 211 Bryant Space Science Center Gainesville Florida 32611 USA Max-Planck-Institut für Extraterrestrische Physik Postfach 1312 Giessenbachstrasse 1 85748 Garching bei München Germany Waterloo Centre for Astrophysics University of Waterloo 200 University Avenue W. Waterloo Ontario N2L 3G1 Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue W. Waterloo Ontario N2L 3G1 Canada Département de Physique Théorique Université de Genève 24 quai Ernest Ansermet 1211 Genève 4 Switzerland
We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the po... 详细信息
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Optimal Neural Summarisation for Full-Field Weak Lensing Cosmological Implicit Inference
arXiv
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arXiv 2024年
作者: Lanzieri, Denise Zeghal, Justine Makinen, T. Lucas Boucaud, Alexandre Starck, Jean-Luc Lanusse, François Université Paris Cité Université Paris-Saclay CEA CNRS AIM Gif-sur-YvetteF-91191 France Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France Astrophysics Group Imperial College London Blackett Laboratory Prince Consort Road LondonSW7 2AZ United Kingdom Université Paris-Saclay Université Paris Cité CEA CNRS AIM Gif-sur-Yvette91191 France Sony Computer Science Laboratories - Rome Joint Initiative CREF-SONY Centro Ricerche Enrico Fermi Via Panisperna 89/A Rome00184 Italy Greece Center for Computational Astrophysics Flatiron Institute 162 5th Ave New YorkNY10010 United States Department of Physics Université de Montréal MontréalH2V 0B3 Canada Mila – Quebec Artificial Intelligence Institute MontréalH2S 3H1 Canada Ciela – Montreal Institute for Astrophysical Data Analysis and Machine Learning MontréalH2V 0B3 Canada
Context. Traditionally, weak lensing cosmological surveys have been analyzed using summary statistics that were either motivated by their analytically tractable likelihoods (e.g. power spectrum), or by their ability t... 详细信息
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LtU-ILI: AN ALL-IN-ONE FRAMEWORK FOR IMPLICIT INFERENCE IN ASTROPHYSICS AND COSMOLOGY
arXiv
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arXiv 2024年
作者: Ho, Matthew Bartlett, Deaglan J. Chartier, Nicolas Cuesta-Lazaro, Carolina Ding, Simon Lapel, Axel Lemos, Pablo Lovell, Christopher C. Makinen, T. Lucas Modi, Chirag Pandya, Viraj Pandey, Shivam Perez, Lucia A. Wandelt, Benjamin Bryan, Greg L. UMR 7095 98 bis bd Arago ParisF-75014 France Center for the Gravitational-Wave Universe Astronomy Program Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Center for Astrophysics Harvard & Smithsonian 60 Garden St CambridgeMA02138 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States 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 Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Institute of Cosmology and Gravitation University of Portsmouth Burnaby Road PortsmouthPO1 3FX United Kingdom & Astrophysics Group Imperial College London Blackett Laboratory Prince Consort Road LondonSW7 2AZ United Kingdom Center for Computational Mathematics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States 4 place Jussieu ParisF-75252 Cedex 5 France
This paper presents the learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology. The ... 详细信息
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Stability evaluation method for special purpose ACS based on sensitivity theory
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AIP Conference Proceedings 2022年 第1期2383卷
作者: Filatov Vladimir Ivanovich Fedorova Veronika Anatolievna Chipchagov Mikhail Sergeevich Zaitsev Mikhail Alekseevich 1Department “Computer security” of faculty “Informatics and control systems” of Bauman Moscow State Technical University 5/1 2ya Baumanskaya st. Moscow 105005 Russia 2Faculty “Big Data Analysis and Machine Learning in Economics and Finance” of Financial University under the Government of the Russian Federation Moscow Russia 3Faculty “Informational system” of Moscow Witte University Moscow Russia
The article deals with the use of complex special purpose automated control systems (ACS), which are characterized by a significant complication of the control process by nodes or elements included in the control loop...
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PSXV-6 Influence of GDF5 Gene Polymorphism on the Concentration of Essential and Toxic Elements in Blood Serum and Milk Productivity of the Holstein Cows
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Journal of Animal Science 2022年 第SUPPLEMENT_3期100卷 212–212页
作者: Zubac, Isidora Sycheva, Irina Komarchev, Alexey Nikitin, Petr Orishev, Aleksandr Vasilyeva, Irina Krasavina, Vera University of Belgrade Russian State Agrarian University–Moscow Timiryazev Agricultural Academy Federal Scientific Center «All-Russian Research and Technological Institute of Poultry» of Russian Academy of Sciences Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)
The aim of this study was to evaluate the effect of GDF5 (growth differentiation factor 5) gene polymorphism on metabolism of chemical elements and milk production of cows. The studies were performed on Holstein cows ... 详细信息
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Robust learning with implicit residual networks
arXiv
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arXiv 2019年
作者: Reshniak, Viktor Webster, Clayton G. Data Analysis and Machine Learning Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Mathematics University of Tennessee at Knoxville KnoxvilleTN37996 United States Lirio LLC KnoxvilleTN37923 United States
In this effort, we propose a new deep architecture utilizing residual blocks inspired by implicit discretization schemes. As opposed to the standard feed-forward networks, the outputs of the proposed implicit residual... 详细信息
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E-service quality from attributes to outcomes: The similarity and difference between digital and hybrid services
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Journal of Open Innovation: Technology, Market, and Complexity 2020年 第4期6卷 1-21页
作者: Vatolkina, Natalia Gorbashko, Elena Kamynina, Nadezhda Fedotkina, Olga Department of Management Bauman Moscow State Technical University (National Research University) Moscow 105005 Russian Federation Department of Project and Quality Management Saint Petersburg State University of Economics St. Petersburg 191023 Russian Federation Department of Land Law and State Registration of Real Estate Moscow State University of Geodesy and Cartography Moscow 105064 Russian Federation Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Moscow 125167 Russian Federation
Our research goal is to offer an e-service quality model based on experience and multidimensional quality and compare its applicability for e-services to find differences and similarities in consumer perceptions and b... 详细信息
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