82 citations · 92 across the 8 of their papers we have counts for
3 papers · 1 filter
Mixture of Polyconvex Neural Potentials for Parametric Hyperelasticity: Towards Foundation Material Models
Steven J. Yang, Govinda Anantha Padmanabha, D. Thomas Seidl +1
Hyperelastic constitutive models enable modeling large deformations in elastic solids. In common practice, a strain energy density function is prescribed in advance and model-speci…
A Bayesian Multiscale Deep Learning Framework for Flows in Random Media
Govinda Anantha Padmanabha, Nicholas Zabaras
Fine-scale simulation of complex systems governed by multiscale partial differential equations (PDEs) is computationally expensive and various multiscale methods have been develope…
Solving inverse problems using conditional invertible neural networks
Govinda Anantha Padmanabha, Nicholas Zabaras
Inverse modeling for computing a high-dimensional spatially-varying property field from indirect sparse and noisy observations is a challenging problem. This is due to the complex…