nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
A dive into spectral inference networks: improved algorithms for self-supervised learning of continuous spectral representations
|
Wu, J. |
|
|
44 |
7 |
p. 1199-1224 |
artikel |
2 |
An artificial viscosity augmented physics-informed neural network for incompressible flow
|
He, Yichuan |
|
|
44 |
7 |
p. 1101-1110 |
artikel |
3 |
Deep convolutional Ritz method: parametric PDE surrogates without labeled data
|
Fuhg, J. N. |
|
|
44 |
7 |
p. 1151-1174 |
artikel |
4 |
Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics
|
Wu, W. |
|
|
44 |
7 |
p. 1039-1068 |
artikel |
5 |
Gaussian process hydrodynamics
|
Owhadi, H. |
|
|
44 |
7 |
p. 1175-1198 |
artikel |
6 |
Peri-Net-Pro: the neural processes with quantified uncertainty for crack patterns
|
Kim, M. |
|
|
44 |
7 |
p. 1085-1100 |
artikel |
7 |
Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving partial differential equations with sharp solutions
|
Mao, Zhiping |
|
|
44 |
7 |
p. 1069-1084 |
artikel |
8 |
Preface: machine-learning approaches for computational mechanics
|
Li, Z. |
|
|
44 |
7 |
p. 1035-1038 |
artikel |
9 |
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures
|
You, H. Q. |
|
|
44 |
7 |
p. 1125-1150 |
artikel |
10 |
Variational inference in neural functional prior using normalizing flows: application to differential equation and operator learning problems
|
Meng, Xuhui |
|
|
44 |
7 |
p. 1111-1124 |
artikel |