MixINN combines mixed models and deep learning to predict genotype-environment interactions in corn trials, yielding 5.8-7.2% higher average yields when selecting top-performing genotypes compared to standard methods.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.
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MixINN: Accelerating Plant Breeding by Combining Mixed Models and Deep Learning for Interaction Prediction
MixINN combines mixed models and deep learning to predict genotype-environment interactions in corn trials, yielding 5.8-7.2% higher average yields when selecting top-performing genotypes compared to standard methods.
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Light-FMP: Lightweight Feature and Model Pruning for Enhanced Deep Recommender Systems
Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.