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Data from title = "Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network", journal = "Computer Methods in Applied Mechanics and Engineering", pages = "112693", year = "2020", issn = "0045-7825", doi = "https://doi.org/10.1016/j.cma.2019.112693", author = "Wu, Ling and Zulueta, Kepa and Major, Zoltan and Arriaga, Aitor and Noels, Ludovic"
sources on https://gitlab.uliege.be/moammm/moammmpublic/tree/master/publicationsData/2020_CMAME_BI_NNW
Multiscale ; Composites ; Bayesian inference ; Neural Network ; Non-linear
Multiscale ; Composites ; Bayesian inference ; Neural Network ; Non-linear
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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