A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems
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Publication:2672767
DOI10.1016/j.jcp.2022.111313OpenAlexW4281392102MaRDI QIDQ2672767
Dimitrios G. Giovanis, Lohit Vandanapu, Michael D. Shields, Katiana Kontolati, Dimitrios Loukrezis
Publication date: 13 June 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.04648
dimension reductionunsupervised learningmanifold learningsurrogate modelinglow-dimensional embeddinghigh-dimensional uncertainty quantification
Artificial intelligence (68Txx) Multivariate analysis (62Hxx) Probabilistic methods, stochastic differential equations (65Cxx)
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