Presentation Open Access
Enhanced Kriging Models within a Bayesian Optimization Framework, to Handle both continuous and Categorical Inputs
Saves, P.; Bartoli, N.; Lefebre, T.; Diouane, Y.; Morlier, J.
Citation Style Language JSON Export
{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.5743339",
"author": [
{
"family": "Saves, P."
},
{
"family": "Bartoli, N."
},
{
"family": "Lefebre, T."
},
{
"family": "Diouane, Y."
},
{
"family": "Morlier, J."
}
],
"issued": {
"date-parts": [
[
2021,
3,
5
]
]
},
"abstract": "<p>SIAM Conference on Computational Science and Engineering</p>\n\n<p>MS130 Derivative-Free Optimization Methods for Solving Expensive Global Black-Box Problems - Part II of II</p>",
"title": "Enhanced Kriging Models within a Bayesian Optimization Framework, to Handle both continuous and Categorical Inputs",
"type": "speech",
"id": "5743339"
}
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| Views | 74 | 74 |
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| Data volume | 399.0 MB | 399.0 MB |
| Unique views | 70 | 70 |
| Unique downloads | 34 | 34 |
Indexed in
- Publication date:
- March 5, 2021
- DOI:
-
- Keyword(s):
- Bayesian optimization kriging
- Grants:
-
European Commission:
- AGILE 4.0 - AGILE 4.0: Towards cyber-physical collaborative aircraft development (815122)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International