5 citations · 11 across the 4 of their papers we have counts for
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cs.LG2022★ 5 cited
Ensembling improves stability and power of feature selection for deep learning models
Prashnna K Gyawali, Xiaoxia Liu, James Zou +1
With the growing adoption of deep learning models in different real-world domains, including computational biology, it is often necessary to understand which data features are esse…
cs.LG2022★ 1 cited
Improving genetic risk prediction across diverse population by disentangling ancestry representations
Prashnna K Gyawali, Yann Le Guen, Xiaoxia Liu +3
Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with sim…