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pro vyhledávání: '"Gemma E. Moran"'
Autor:
Venkateswaran Shekar, Vincent Yu, Benjamin J. Garcia, David Benjamin Gordon, Gemma E. Moran, David M. Blei, Loïc M. Roch, Alberto García-Durán, Mansoor Ani Najeeb, Margaret Zeile, Philip W. Nega, Zhi Li, Mina A. Kim, Emory M. Chan, Alexander J. Norquist, Sorelle Friedler, Joshua Schrier
Machine learning is a useful tool for accelerating materials discovery, however it is a challenge to develop accurate methods that successfully transfer between domains while also broadening the scope of reaction conditions considered. In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9b7d8eb73803574e204f28241acb281
https://doi.org/10.26434/chemrxiv-2022-l1wpf-v2
https://doi.org/10.26434/chemrxiv-2022-l1wpf-v2
Publikováno v:
The Annals of Applied Statistics. 15
Biclustering methods simultaneously group samples and their associated features. In this way, biclustering methods differ from traditional clustering methods, which utilize the entire set of features to distinguish groups of samples. Motivating appli
Publikováno v:
Bayesian Anal. 14, no. 4 (2019), 1091-1119
Consider the problem of high dimensional variable selection for the Gaussian linear model when the unknown error variance is also of interest. In this paper, we show that the use of conjugate shrinkage priors for Bayesian variable selection can have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dcd1362d18f13b9aed666616d74f41b7
http://arxiv.org/abs/1801.03019
http://arxiv.org/abs/1801.03019