most citedGaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids

31 citations · 31 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CE2024★ 31 cited

Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids

Saurabh Deshpande, Hussein Rappel, Mark Hobbs +2

Many real-world applications demand accurate and fast predictions, as well as reliable uncertainty estimates. However, quantifying uncertainty on high-dimensional predictions is st…