CIMMYT Research Data & Software Repository Network

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Contributor Name: CGIAR Research Program on Wheat (WHEAT) Subject: Agricultural Sciences Keyword Term: Maize Keyword Term: Agricultural research Contributor Name: CGIAR Keyword Term: GBLUP

1 to 2 of 2 Results

Dataset / Software Deep kernel of genomic and near infrared predictions in multi-environment breeding trials Jul 18, 2019 - CIMMYT Research Data Cuevas, Jaime; Montesinos-López, Osval A; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", hdl:11529/10548180, CIMMYT Research Data & Software Repository Network, V4 In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...
Dataset / Software A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data Oct 26, 2018 - CIMMYT Research Data Montesinos-López, Osval A ; Montesinos-López, Abelardo; Crossa, Jose; Cuevas, Jaime; Montesinos-López, José Cricelio; Gutiérrez, Zitlalli Salas; Lillemo, Morten; Juliana, Philomin; Singh, Ravi, 2018, "A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data", hdl:11529/10548141, CIMMYT Research Data & Software Repository Network, V1 A new statistical model is presented for genomic prediction on maize and wheat data comprising multi-trait, multi-environment data.

Dataset / Software

Deep kernel of genomic and near infrared predictions in multi-environment breeding trials

Jul 18, 2019 - CIMMYT Research Data

Cuevas, Jaime; Montesinos-López, Osval A; Juliana, Philomin; Pérez-Rodríguez, Paulino; Burgueño, Juan; Guzman, Carlos; Montesinos-López, Abelardo; Crossa, Jose, 2019, "Deep kernel of genomic and near infrared predictions in multi-environment breeding trials", hdl:11529/10548180, CIMMYT Research Data & Software Repository Network, V4

In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel met...

Dataset / Software

A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data

Oct 26, 2018 - CIMMYT Research Data

Montesinos-López, Osval A ; Montesinos-López, Abelardo; Crossa, Jose; Cuevas, Jaime; Montesinos-López, José Cricelio; Gutiérrez, Zitlalli Salas; Lillemo, Morten; Juliana, Philomin; Singh, Ravi, 2018, "A Bayesian genomic multi-output regressor stacking model for predicting multi-trait multi-environment plant breeding data", hdl:11529/10548141, CIMMYT Research Data & Software Repository Network, V1

A new statistical model is presented for genomic prediction on maize and wheat data comprising multi-trait, multi-environment data.

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