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researcher

S. Mo

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • stat.ML2
  • physics.comp-ph1
same name
  • S. Mo — 30 papers, h 53
  • S. Mo — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedDeep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification

289 citations · 289 across the 1 of their papers we have counts for

collaborators

3 papers

physics.comp-ph2019

Integration of adversarial autoencoders with residual dense convolutional networks for estimation of non-Gaussian hydraulic conductivities

Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi +1

Inverse modeling for the estimation of non-Gaussian hydraulic conductivity fields in subsurface flow and solute transport models remains a challenging problem. This is mainly due t…

stat.ML2018★ 289 cited

Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification

Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi +1

Identification of a groundwater contaminant source simultaneously with the hydraulic conductivity in highly-heterogeneous media often results in a high-dimensional inverse problem.…

stat.ML2018

Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media

Shaoxing Mo, Yinhao Zhu, Nicholas Zabaras +2

Surrogate strategies are used widely for uncertainty quantification of groundwater models in order to improve computational efficiency. However, their application to dynamic multip…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.