Name
Abstract | ||
|---|---|---|
•This paper introduces a novel Weak Constraint Gaussian Process (WCGP) model.•We integrate noisy inputs into the classical Gaussian Process (GP) predictive distribution.•In this paper, the WCGP model is used for an optimal sensor placement problem.•We provide experimental results for pollutant dispersion within a real urban environment. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.jocs.2020.101110 | Journal of Computational Science |
Keywords | DocType | Volume |
Gaussian Processes,Sensor placement,Data assimilation,Parallel algorithms,Big data | Journal | 42 |
ISSN | Citations | PageRank |
1877-7503 | 1 | 0.35 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tolga Hasan Dur | 1 | 1 | 0.35 |
| Rossella Arcucci | 2 | 22 | 5.64 |
| Laetitia Mottet | 3 | 1 | 0.69 |
| Miguel Molina-Solana | 4 | 48 | 12.80 |
| Christopher Pain | 5 | 1 | 0.35 |
| Yike Guo | 6 | 1319 | 165.32 |