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Equivariant geometric learning for digital rock physics: estimating
formation factor and effective permeability tensors from Morse graph

v1v2v3 (latest)

Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph

International Journal for Multiscale Computational Engineering (IJMCE), 2021

12 April 2021

Nikolaos N. Vlassis

ArXiv (abs)PDF HTML

Papers citing "Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph"

9 / 9 papers shown

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms

Benjamin Shaffer

Elizabeth Armstrong

Nathaniel Trask

208

4

0

09 Aug 2025

Towards scientific machine learning for granular material simulations -- challenges and opportunities

Towards scientific machine learning for granular material simulations -- challenges and opportunitiesArchives of Computational Methods in Engineering (ACME), 2025

Daniel N. Wilke

...

369

8

0

01 Apr 2025

CNN-powered micro- to macro-scale flow modeling in deformable porous media

CNN-powered micro- to macro-scale flow modeling in deformable porous media

Wolfgang Ehlers

144

0

0

11 Jan 2025

Improving the performance of Stein variational inference through extreme
sparsification of physically-constrained neural network models

Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models

G. A. Padmanabha

384

12

0

30 Jun 2024

Equivariant graph convolutional neural networks for the representation
of homogenized anisotropic microstructural mechanical response

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response

235

3

0

05 Apr 2024

e3nn: Euclidean Neural Networks

e3nn: Euclidean Neural Networks

248

265

0

18 Jul 2022

Generative Coarse-Graining of Molecular Conformations

Generative Coarse-Graining of Molecular ConformationsInternational Conference on Machine Learning (ICML), 2022

Benjamin Kurt Miller

Jian Tang

Rafael Gómez-Bombarelli

257

47

0

28 Jan 2022

Equivariant Subgraph Aggregation Networks

Equivariant Subgraph Aggregation Networks

Beatrice Bevilacqua

Fabrizio Frasca

497

216

0

06 Oct 2021

Training multi-objective/multi-task collocation physics-informed neural
network with student/teachers transfer learnings

Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings

286

21

0

24 Jul 2021

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