# ORTHOGONAL BASES FOR POLYNOMIAL REGRES- SION WITH DERIVATIVE INFORMATION IN UNCER- TAINTY QUANTIFICATION

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/orthogonal-bases-for-polynomial-regres-sion-with-derivative-information-in-uncer/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yiou Li,Mihai Anitescu,Oleg Roderick,Fred J. Hickernell |
| Citations | 0 |
| Fields | Computer Science,Decision Sciences,Physics and Astronomy |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2403454522 |
| Type | article |
| Year | 2010 |

## Paper authors

- [Yiou Li](https://scholariq.org/researchers/yiou-li/)

## Paper primary topic

- [Probabilistic and Robust Engineering Design](https://scholariq.org/topics/probabilistic-and-robust-engineering-design/)

## Paper topics

- [Probabilistic and Robust Engineering Design](https://scholariq.org/topics/probabilistic-and-robust-engineering-design/)
- [Model Reduction and Neural Networks](https://scholariq.org/topics/model-reduction-and-neural-networks/)
- [Advanced Multi-Objective Optimization Algorithms](https://scholariq.org/topics/advanced-multi-objective-optimization-algorithms/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.