Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Daniel Iong"'
Publikováno v:
Data Science in Science, Vol 3, Iss 1 (2024)
Gaussian Processes (GP) have become popular machine learning methods for kernel based learning on datasets with complicated covariance structures. In this paper, we present a novel extension to the GP framework using a contaminated normal likelihood
Externí odkaz:
https://doaj.org/article/e2a23ac3d1604297a08d7176ee09d36c
Autor:
Aniket Jivani, Nishtha Sachdeva, Zhenguang Huang, Yang Chen, Bart van der Holst, Ward Manchester, Daniel Iong, Hongfan Chen, Shasha Zou, Xun Huan, Gabor Toth
Publikováno v:
Space Weather. 21
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4457e3e5002b7bf3871d99d199294254
https://doi.org/10.1029/2022sw003262
https://doi.org/10.1029/2022sw003262
Autor:
Daniel Iong, Yang Chen, Gabor Toth, Shasha Zou, Tuija Pulkkinen, Jiaen Ren, Enrico Camporeale, Tamas Gombosi
Publikováno v:
Space Weather. 20
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::222174dcaf71cbd6b42f33391d9d532f
https://doi.org/10.1029/2021sw002928
https://doi.org/10.1029/2021sw002928
Autor:
Daniel Iong, Yang Chen, Gabor Toth, Shasha Zou, Tuija I. Pulkkinen, Jiaen Ren, Enrico Camporeale, Tamas I. I. Gombosi
In this work, we develop gradient boosting machines (GBMs) for forecasting the SYM-H index multiple hours ahead using different combinations of solar wind and interplanetary magnetic field (IMF) pa...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f5f295bdb47ac04a3aca08414827f6f
https://doi.org/10.1002/essoar.10508063.1
https://doi.org/10.1002/essoar.10508063.1
