| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A perspective on regression and Bayesian approaches for system identification of pattern formation dynamics
|
Wang, Zhenlin
|
|
|
10 |
3 |
p. 188-194
|
artikel
|
| 2 |
Classifying wakes produced by self-propelled fish-like swimmers using neural networks
|
Li, Binglin
|
|
|
10 |
3 |
p. 149-154
|
artikel
|
| 3 |
Deep density estimation via invertible block-triangular mapping
|
Tang, Keju
|
|
|
10 |
3 |
p. 143-148
|
artikel
|
| 4 |
Learning material law from displacement fields by artificial neural network
|
Yang, Hang
|
|
|
10 |
3 |
p. 202-206
|
artikel
|
| 5 |
Mechanistic Machine Learning: Theory, Methods, and Applications
|
|
|
|
10 |
3 |
p. 141-142
|
artikel
|
| 6 |
Multi-fidelity Gaussian process based empirical potential development for Si:H nanowires
|
Kim, Moonseop
|
|
|
10 |
3 |
p. 195-201
|
artikel
|
| 7 |
Nonnegativity-enforced Gaussian process regression
|
Pensoneault, Andrew
|
|
|
10 |
3 |
p. 182-187
|
artikel
|
| 8 |
Physics-constrained bayesian neural network for fluid flow reconstruction with sparse and noisy data
|
Sun, Luning
|
|
|
10 |
3 |
p. 161-169
|
artikel
|
| 9 |
Physics-constrained indirect supervised learning
|
Chen, Yuntian
|
|
|
10 |
3 |
p. 155-160
|
artikel
|
| 10 |
Physics-informed deep learning for incompressible laminar flows
|
Rao, Chengping
|
|
|
10 |
3 |
p. 207-212
|
artikel
|
| 11 |
Reducing parameter space for neural network training
|
Qin, Tong
|
|
|
10 |
3 |
p. 170-181
|
artikel
|
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