31 citations · 31 across the 2 of their papers we have counts for
2 papers
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…
math.NA2022
A probabilistic peridynamic framework with an application to the study of the statistical size effect
Mark Hobbs, Hussein Rappel, Tim Dodwell
Mathematical models are essential for understanding and making predictions about systems arising in nature and engineering. Yet, mathematical models are a simplification of true ph…