236 citations · 253 across the 3 of their papers we have counts for
3 papers
cs.CE2021
MD-inferred neural network monoclinic finite-strain hyperelasticity models for -HMX: Sobolev training and validation against physical constraints
Nikolaos N. Vlassis, Puhan Zhao, Ran Ma +2
We present a machine learning framework to train and validate neural networks to predict the anisotropic elastic response of the monoclinic organic molecular crystal -HMX in the…
physics.geo-ph2021★ 17 cited
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
Chen Cai, Nikolaos Vlassis, Lucas Magee +6
We present a SE(3)-equivariant graph neural network (GNN) approach that directly predicting the formation factor and effective permeability from micro-CT images. FFT solvers are es…
cs.LG2020★ 236 cited
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity
Nikolaos Vlassis, Ran Ma, WaiChing Sun
This paper is the first attempt to use geometric deep learning and Sobolev training to incorporate non-Euclidean microstructural data such that anisotropic hyperelastic material ma…