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20162019
most citedDeep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

485 citations · 652 across the 4 of their papers we have counts for

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Showing 2019Show all

2 papers · 1 filter

physics.comp-ph2019★ 1 cited

Deep active subspaces - a scalable method for high-dimensional uncertainty propagation

Rohit Tripathy, Ilias Bilionis

A problem of considerable importance within the field of uncertainty quantification (UQ) is the development of efficient methods for the construction of accurate surrogate models.…

physics.data-an2019★ 164 cited

Simulator-free Solution of High-Dimensional Stochastic Elliptic Partial Differential Equations using Deep Neural Networks

Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis +1

Stochastic partial differential equations (SPDEs) are ubiquitous in engineering and computational sciences. The stochasticity arises as a consequence of uncertainty in input parame…