nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
A continuous convolutional trainable filter for modelling unstructured data
|
Coscia, Dario |
|
|
72 |
2 |
p. 253-265 |
artikel |
2 |
A non-intrusive approach for physics-constrained learning with application to fuel cell modeling
|
Srivastava, Vishal |
|
|
72 |
2 |
p. 411-430 |
artikel |
3 |
A structure-preserving neural differential operator with embedded Hamiltonian constraints for modeling structural dynamics
|
Najera-Flores, David A. |
|
|
72 |
2 |
p. 241-252 |
artikel |
4 |
Convolution hierarchical deep-learning neural network (C-HiDeNN) with graphics processing unit (GPU) acceleration
|
Park, Chanwook |
|
|
72 |
2 |
p. 383-409 |
artikel |
5 |
Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond
|
Lu, Ye |
|
|
72 |
2 |
p. 333-362 |
artikel |
6 |
Convolution Hierarchical Deep-Learning Neural Network Tensor Decomposition (C-HiDeNN-TD) for high-resolution topology optimization
|
Li, Hengyang |
|
|
72 |
2 |
p. 363-382 |
artikel |
7 |
Deep Learning Discrete Calculus (DLDC): a family of discrete numerical methods by universal approximation for STEM education to frontier research
|
Saha, Sourav |
|
|
72 |
2 |
p. 311-331 |
artikel |
8 |
Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations
|
Goraya, Shoaib |
|
|
72 |
2 |
p. 267-289 |
artikel |
9 |
Mallat Scattering Transformation based surrogate for Magnetohydrodynamics
|
Glinsky, Michael E. |
|
|
72 |
2 |
p. 291-309 |
artikel |