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cs.LG2025
Biology-informed neural networks learn nonlinear representations from omics data to improve genomic prediction and interpretability
Katiana Kontolati, Rini Jasmine Gladstone, Ian Davis +1
We extend biologically-informed neural networks (BINNs) for genomic prediction (GP) and selection (GS) in crops by integrating thousands of single-nucleotide polymorphisms (SNPs) w…
cs.LG2024
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models
Ethan Pickering, Themistoklis P. Sapsis
Misleading or unnecessary data can have out-sized impacts on the health or accuracy of Machine Learning (ML) models. We present a Bayesian sequential selection method, akin to Baye…