Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification. (arXiv:2201.07753v1 [stat.ML])

We propose a novel \textit{capsule} based deep encoder-decoder model for
surrogate modeling and uncertainty quantification of systems in mechanics from
sparse data. The proposed framework is developed by adapting Capsule Network
(CapsNet) architecture into image-to-image regression encoder-decoder network.
Specifically, the aim is to exploit the benefits of CapsNet over convolution
neural network (CNN) $-$ retaining pose and position information related to an
entity to name a few. The performance of proposed approach is illustrated by
solving an elliptic stochastic partial …

arxiv encoder-decoder ml modeling network uncertainty