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ISSN Print: 2689-3967
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Текущий годТом 5, 2024 / Выпуск 4SPECIAL ISSUE: ADVANCEMENTS AND APPLICATIONS OF MULTIFIDELITY MACHINE LEARNING IN ENGINEERING DOI: 10.1615/JMachLearnModelComput.v5.i4 Table of Contents:
MESH REFINEMENT AS PROBABILISTIC LEARNING
Philippe Hawi, Roger Ghanem
Philippe Hawi
Roger Ghanem DOI: 10.1615/JMachLearnModelComput.2024054830
ROBUST TOPOLOGY OPTIMIZATION USING MULTI-FIDELITY VARIATIONAL AUTOENCODERS
Rini Jasmine Gladstone, Mohammad Amin Nabian, Vahid Keshavarzzadeh, Hadi Meidani
Rini Jasmine Gladstone
Mohammad Amin Nabian
Vahid Keshavarzzadeh
Hadi Meidani DOI: 10.1615/JMachLearnModelComput.2024054646
HYBRID CHANCE-CONSTRAINED OPTIMAL POWER FLOW UNDER LOAD AND RENEWABLE GENERATION UNCERTAINTY USING ENHANCED MULTI-FIDELITY GRAPH NEURAL NETWORKS
Kamiar Khayambashi, Md Abul Hasnat, Negin Alemazkoor
Kamiar Khayambashi
Md Abul Hasnat
Negin Alemazkoor DOI: 10.1615/JMachLearnModelComput.2024054885
MULTI-FIDELITY MACHINE LEARNING FOR UNCERTAINTY QUANTIFICATION AND OPTIMIZATION
Ruda Zhang, Negin Alemazkoor
Ruda Zhang
Negin Alemazkoor DOI: 10.1615/JMachLearnModelComput.2024055786
DESIGN OF EXPERIMENTS VIA MULTI-FIDELITY SURROGATES AND STATISTICAL SENSITIVITY MEASURES
David J. Gillcrist, Negin Alemazkoor, Yanlai Chen, Mazdak Tootkaboni
David J. Gillcrist
Negin Alemazkoor
Yanlai Chen
Mazdak Tootkaboni DOI: 10.1615/JMachLearnModelComput.2024055261
INDEX, VOLUME 5, 2024
123-126 страниц
DOI: 10.1615/JMachLearnModelComput.v5.i4.60 |
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