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GAN to 'reconstruct' sthocastic heterogeneous materials
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创建时间：
2023-03-09
相关数据集
Data for: Overcoming the drawbacks of plastic strain estimation based on KAM
Electron backscatter diffraction data sets used in this work. The files named 00, 03, 06, 09, 12 and 15.ctf are from the reference specimens, and the filenames represent the approximate nominal plasti
NIAID Data Ecosystem140
Sanjiangyuan
we selected the Three Rivers Source region in the heart of the Qinghai-Tibet Plateau to construct a test set to verify the robustness of SMGAN in complex environments. This region has varied terrain a
魔搭社区2025-08-08 更新40
HTGAN: heavy-tail GAN for multivariate dependent extremes via latent-dimensional control
Dealing with extreme values is a key challenge in probabilistic modeling, relevant to economics, engineering, and life sciences. Standard GANs, built on light-tailed noise, fail to capture heavy-tail
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Fig.8.tif
Fig.8. Microstructure analysis: (a) the morphologies of the four-pass FSPed AMCs, (b) the main element profiles by EDS line scan detection in (a), (c) EDS results of the marked point A in (a).
Figshare2018-06-10 更新80
Table2_Generative Adversarial Networks–Enabled Human–Artificial Intelligence Collaborative Applications for Creative and Design Industries: A Systematic Review of Current Approaches and Trends.DOC
The future of work and workplace is very much in flux. A vast amount has been written about artificial intelligence (AI) and its impact on work, with much of it focused on automation and its impact in
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