Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep convolutional neural networks for uncertainty propagation in random
  fields   The development of a reliable and robust surrogate model is often constrained
by the dimensionality of the problem. For a system with high-dimensional
inputs/outputs (I/O), conventional approaches usually use a low-dimensional
manifold to describe the high-dimensional system, where the I/O data is first
reduced to more manageable dimensions and then the condensed representation is
used for surrogate modeling. In this study, we present a new solution scheme
for this type of problems based on a deep learning approach. The proposed
surrogate is based on a particular network architecture, i.e. the convolutional
neural networks. The surrogate architecture is designed in a hierarchical style
containing three different levels of model structures, advancing the efficiency
and effectiveness of the model in the aspect of training and deploying. To
assess the model performance, we carry out uncertainty quantification in a
continuum mechanics benchmark problem. Numerical results suggest the proposed
model is capable of directly inferring a wide variety of I/O mapping
relationships. Uncertainty analysis results obtained via the proposed surrogate
have successfully characterized the statistical properties of the output fields
compared to the Monte Carlo estimates.

28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex