Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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1 |
Material Type: Livro
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Gaussian Processes for Machine LearningRasmussen, Carl Edward ; Williams, Christopher K. ICambridge: MIT Press 2005Texto completo disponível |
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2 |
Material Type: Artigo
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Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow ProblemsTartakovsky, A. M. ; Marrero, C. Ortiz ; Perdikaris, Paris ; Tartakovsky, G. D. ; Barajas‐Solano, D.Water resources research, 2020-05, Vol.56 (5), p.n/a [Periódico revisado por pares]Washington: John Wiley & Sons, IncTexto completo disponível |
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3 |
Material Type: Artigo
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Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s NextCuomo, Salvatore ; Di Cola, Vincenzo Schiano ; Giampaolo, Fabio ; Rozza, Gianluigi ; Raissi, Maziar ; Piccialli, FrancescoJournal of scientific computing, 2022-09, Vol.92 (3), p.88, Article 88 [Periódico revisado por pares]New York: Springer USTexto completo disponível |
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4 |
Material Type: Artigo
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Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron modelHuang, Faming ; Cao, Zhongshan ; Jiang, Shui-Hua ; Zhou, Chuangbing ; Huang, Jinsong ; Guo, ZizhengLandslides, 2020-12, Vol.17 (12), p.2919-2930 [Periódico revisado por pares]Berlin/Heidelberg: Springer Berlin HeidelbergTexto completo disponível |
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5 |
Material Type: Artigo
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Four Generations of High-Dimensional Neural Network PotentialsBehler, JörgChemical reviews, 2021-08, Vol.121 (16), p.10037-10072 [Periódico revisado por pares]United States: American Chemical SocietyTexto completo disponível |
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6 |
Material Type: Artigo
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Interpretable machine learning: Fundamental principles and 10 grand challengesRudin, Cynthia ; Chen, Chaofan ; Chen, Zhi ; Huang, Haiyang ; Semenova, Lesia ; Zhong, ChudiStatistics surveys, 2022-01, Vol.16 (none) [Periódico revisado por pares]Texto completo disponível |
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7 |
Material Type: Artigo
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sGDML: Constructing accurate and data efficient molecular force fields using machine learningChmiela, Stefan ; Sauceda, Huziel E. ; Poltavsky, Igor ; Müller, Klaus-Robert ; Tkatchenko, AlexandreComputer physics communications, 2019-07, Vol.240, p.38-45 [Periódico revisado por pares]Elsevier B.VTexto completo disponível |
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8 |
Material Type: Artigo
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Rapid Characterization of the July 2019 Ridgecrest, California, Earthquake Sequence From Raw Seismic Data Using Machine‐Learning Phase PickerLiu, Min ; Zhang, Miao ; Zhu, Weiqiang ; Ellsworth, William L. ; Li, HongyiGeophysical research letters, 2020-02, Vol.47 (4), p.n/a [Periódico revisado por pares]WileyTexto completo disponível |
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Material Type: Artigo
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Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning methodChen, Yuntian ; Huang, Dou ; Zhang, Dongxiao ; Zeng, Junsheng ; Wang, Nanzhe ; Zhang, Haoran ; Yan, JinyueJournal of computational physics, 2021-11, Vol.445, p.110624, Article 110624 [Periódico revisado por pares]Cambridge: Elsevier IncTexto completo disponível |
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10 |
Material Type: Artigo
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Active learning machine learns to create new quantum experimentsMelnikov, Alexey A. ; Nautrup, Hendrik Poulsen ; Krenn, Mario ; Dunjko, Vedran ; Tiersch, Markus ; Zeilinger, Anton ; Briegel, Hans J.Proceedings of the National Academy of Sciences - PNAS, 2018-02, Vol.115 (6), p.1221-1226 [Periódico revisado por pares]United States: National Academy of SciencesTexto completo disponível |