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Material Type: Bài báo
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The State of the Art in Enhancing Trust in Machine Learning Models with the Use of VisualizationsComputer graphics forum, 2020-06, Vol.39 (3), p.713-756 [Tạp chí có phản biện]Attribution ;ISSN: 0167-7055 ;EISSN: 1467-8659 ;DOI: 10.1111/cgf.14034Tài liệu số/Tài liệu điện tử |
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Material Type: Kỷ yếu hội nghị
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CC2Vec: Distributed Representations of Code ChangesDistributed under a Creative Commons Attribution 4.0 International License ;DOI: 10.1145/3377811.3380361Tài liệu số/Tài liệu điện tử |
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3 |
Material Type: Bài báo
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAIIEEE transaction on neural networks and learning systems, 2021-11, Vol.32 (11), p.4793-4813ISSN: 2162-237X ;EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2020.3027314 ;PMID: 33079674 ;CODEN: ITNNALTài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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Multi-Input data ASsembly for joint AnalysisPloS one, 2024-05, Vol.19 (5), p.e0302425 [Tạp chí có phản biện]COPYRIGHT 2024 Public Library of Science ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0302425Tài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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Correction: Impacts of multicollinearity on CAPT modalities: An heterogeneous machine learning framework for computer-assisted French phoneme pronunciation trainingPloS one, 2023-10, Vol.18 (10), p.e0292513-e0292513 [Tạp chí có phản biện]COPYRIGHT 2023 Public Library of Science ;2023 Bi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 Bi et al 2023 Bi et al ;2023 Bi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0292513Tài liệu số/Tài liệu điện tử |
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Material Type: Sách
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Gaussian Processes for Machine Learning2005 Massachusetts Institute of Technology ;2005 MIT This content is available without a subscription. It may not be altered in any way and proper attribution is required. ;ISBN: 9780262256834 ;ISBN: 026218253X ;ISBN: 9780262182539 ;ISBN: 0262256835 ;EISBN: 9780262256834 ;EISBN: 0262256835 ;EISBN: 0262261073 ;EISBN: 9780262261074 ;DOI: 10.7551/mitpress/3206.001.0001 ;OCLC: 68194203 ;LCCallNum: QA274.4 .R37 2006ebTài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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A Machine Learning Model Based on GRU and LSTM to Predict the Environmental Parameters in a Layer House, Taking CO[sub.2] Concentration as an ExampleSensors (Basel, Switzerland), 2023-12, Vol.24 (1) [Tạp chí có phản biện]COPYRIGHT 2023 MDPI AG ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s24010244Tài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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Correction: Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinomaBMC medicine, 2024-04, Vol.22 (1), p.179-179 [Tạp chí có phản biện]COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1741-7015 ;EISSN: 1741-7015 ;DOI: 10.1186/s12916-024-03404-0 ;PMID: 38679726Tài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow ProblemsWater resources research, 2020-05, Vol.56 (5), p.n/a [Tạp chí có phản biện]2020. American Geophysical Union. All Rights Reserved. ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1029/2019WR026731Tài liệu số/Tài liệu điện tử |
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Material Type: Bài báo
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Peering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning MethodsAmerican journal of roentgenology (1976), 2019-01, Vol.212 (1), p.38-43 [Tạp chí có phản biện]ISSN: 0361-803X ;EISSN: 1546-3141 ;DOI: 10.2214/AJR.18.20224 ;PMID: 30332290Tài liệu số/Tài liệu điện tử |