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20192025
most citedStructure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression

3 citations · 3 across the 4 of their papers we have counts for

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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.LG2022★ 3 cited

Structure and Distribution Metric for Quantifying the Quality of Uncertainty: Assessing Gaussian Processes, Deep Neural Nets, and Deep Neural Operators for Regression

Ethan Pickering, Themistoklis P. Sapsis

We propose two bounded comparison metrics that may be implemented to arbitrary dimensions in regression tasks. One quantifies the structure of uncertainty and the other quantifies…